Up next in 10
Mobile testing is being redefined by AI-driven automation. Enterprises across finance, retail, healthcare, telecom, and travel are reporting dramatic improvements in both quality and speed — and this session shows you how.
In this talk, we reveal how 500+ organizations are reshaping their mobile testing strategies with AI-powered frameworks and automation pipelines.
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0:00
The mobile testing landscape has
0:02
The mobile testing landscape has
0:02
The mobile testing landscape has fundamentally shifted with AIdriven
0:04
fundamentally shifted with AIdriven
0:04
fundamentally shifted with AIdriven automation now delivering measurable ROI
0:06
automation now delivering measurable ROI
0:06
automation now delivering measurable ROI across industries. Learn in this episode
0:08
across industries. Learn in this episode
0:08
across industries. Learn in this episode of AI dev tools about AI powered mobile
0:11
of AI dev tools about AI powered mobile
0:11
of AI dev tools about AI powered mobile testing. And joining us today is Chan
0:14
testing. And joining us today is Chan
0:14
testing. And joining us today is Chan Singh who's automation lead architect at
0:17
Singh who's automation lead architect at
0:17
Singh who's automation lead architect at Hi Chan and welcome to the show.
0:20
Hi Chan and welcome to the show.
0:20
Hi Chan and welcome to the show. [Music]
0:25
Hello Simon. Uh thank you very much for
0:27
Hello Simon. Uh thank you very much for
0:27
Hello Simon. Uh thank you very much for giving me this opportunity. So uh let's
0:31
giving me this opportunity. So uh let's
0:31
giving me this opportunity. So uh let's get started. I'm sharing my screen. So
0:35
get started. I'm sharing my screen. So
0:35
get started. I'm sharing my screen. So okay let's move on. As we know you know
0:37
okay let's move on. As we know you know
0:37
okay let's move on. As we know you know this is AI powered mobile test
0:39
this is AI powered mobile test
0:39
this is AI powered mobile test revolution. This is the first slide.
0:41
revolution. This is the first slide.
0:41
revolution. This is the first slide. Let's move on to uh second slide.
0:45
Let's move on to uh second slide.
0:45
Let's move on to uh second slide. So I would like to you know first uh
0:47
So I would like to you know first uh
0:47
So I would like to you know first uh talk on you know uh highlighting the
0:49
talk on you know uh highlighting the
0:49
talk on you know uh highlighting the traditional approaches that we are using
0:51
traditional approaches that we are using
0:51
traditional approaches that we are using right now. uh right now you know as a
0:54
right now. uh right now you know as a
0:54
right now. uh right now you know as a part of this traditional approaches we
0:55
part of this traditional approaches we
0:55
part of this traditional approaches we have lot of you know bottlenecks as such
0:58
have lot of you know bottlenecks as such
0:58
have lot of you know bottlenecks as such uh when we do manual testing so manual
1:01
uh when we do manual testing so manual
1:01
uh when we do manual testing so manual bottlenecks you know generally slow down
1:02
bottlenecks you know generally slow down
1:02
bottlenecks you know generally slow down the process and uh in in mobile
1:06
the process and uh in in mobile
1:06
the process and uh in in mobile automation you know uh if if we have you
1:08
automation you know uh if if we have you
1:08
automation you know uh if if we have you know manual uh things right so limited
1:11
know manual uh things right so limited
1:11
know manual uh things right so limited device coverage as such right so if I'm
1:13
device coverage as such right so if I'm
1:13
device coverage as such right so if I'm doing manually obviously I have four
1:16
doing manually obviously I have four
1:16
doing manually obviously I have four five devices in hand and I'm going to uh
1:19
five devices in hand and I'm going to uh
1:19
five devices in hand and I'm going to uh limit myself right so this is another
1:22
limit myself right so this is another
1:22
limit myself right so this is another you pain point in u uh mobile automation
1:25
you pain point in u uh mobile automation
1:25
you pain point in u uh mobile automation in mobile testing basically and then you
1:27
in mobile testing basically and then you
1:28
in mobile testing basically and then you know we have these feedbacks right uh
1:30
know we have these feedbacks right uh
1:30
know we have these feedbacks right uh feedback delays are always there right
1:32
feedback delays are always there right
1:32
feedback delays are always there right feedback loops are delayed slowing down
1:34
feedback loops are delayed slowing down
1:34
feedback loops are delayed slowing down resolution and all those things and then
1:38
resolution and all those things and then
1:38
resolution and all those things and then you you know we have this high resource
1:40
you you know we have this high resource
1:40
you you know we have this high resource uh dependency as well so obviously you
1:43
uh dependency as well so obviously you
1:43
uh dependency as well so obviously you know we always have a uh we are uh we
1:46
know we always have a uh we are uh we
1:46
know we always have a uh we are uh we don't have you know resources easily
1:48
don't have you know resources easily
1:48
don't have you know resources easily available for uh mobile testing as such
1:51
available for uh mobile testing as such
1:51
available for uh mobile testing as such so we always have dependency on large QA
1:53
so we always have dependency on large QA
1:53
so we always have dependency on large QA teams. Okay, QA resources available, not
1:56
teams. Okay, QA resources available, not
1:56
teams. Okay, QA resources available, not available, right? So these are you know
1:59
available, right? So these are you know
1:59
available, right? So these are you know some of the bottlenecks and we are just
2:02
some of the bottlenecks and we are just
2:02
some of the bottlenecks and we are just trying to shift uh shift mobile testing
2:04
trying to shift uh shift mobile testing
2:04
trying to shift uh shift mobile testing landscape to you know mobile manual to
2:08
landscape to you know mobile manual to
2:08
landscape to you know mobile manual to you know mobile automation using various
2:10
you know mobile automation using various
2:10
you know mobile automation using various clouds as well as we will be using AI
2:13
clouds as well as we will be using AI
2:13
clouds as well as we will be using AI into those clouds uh which will really
2:15
into those clouds uh which will really
2:15
into those clouds uh which will really transform uh our mobile testing journey
2:18
transform uh our mobile testing journey
2:18
transform uh our mobile testing journey as such right so so AIdriven
2:21
as such right so so AIdriven
2:21
as such right so so AIdriven transformation so what we are trying to
2:23
transformation so what we are trying to
2:23
transformation so what we are trying to do here is focus testing where it's most
2:26
do here is focus testing where it's most
2:26
do here is focus testing where it's most needed intelligent testing
2:27
needed intelligent testing
2:27
needed intelligent testing prioritization right that is it requires
2:30
prioritization right that is it requires
2:30
prioritization right that is it requires a focus testing uh where we can focus on
2:33
a focus testing uh where we can focus on
2:33
a focus testing uh where we can focus on you know what all the critical paths are
2:34
you know what all the critical paths are
2:34
you know what all the critical paths are for mobile uh testing as such then we
2:38
for mobile uh testing as such then we
2:38
for mobile uh testing as such then we have predictive defect uh detection so
2:40
have predictive defect uh detection so
2:40
have predictive defect uh detection so here we are just trying to you know spot
2:43
here we are just trying to you know spot
2:43
here we are just trying to you know spot the issues up front okay so possibility
2:45
the issues up front okay so possibility
2:45
the issues up front okay so possibility is you know we can uh using this
2:48
is you know we can uh using this
2:48
is you know we can uh using this AIdriven transformation uh and
2:50
AIdriven transformation uh and
2:50
AIdriven transformation uh and automation we can you know spot on the
2:53
automation we can you know spot on the
2:53
automation we can you know spot on the issue well in advance then automated
2:56
issue well in advance then automated
2:56
issue well in advance then automated cross platform validation. So basically
2:59
cross platform validation. So basically
3:00
cross platform validation. So basically you know I if I'm testing once I can
3:03
you know I if I'm testing once I can
3:03
you know I if I'm testing once I can test on various other platforms as such
3:06
test on various other platforms as such
3:06
test on various other platforms as such right so using this AIdriven you know
3:08
right so using this AIdriven you know
3:08
right so using this AIdriven you know and automation clouds as such right it
3:11
and automation clouds as such right it
3:11
and automation clouds as such right it is easy to achieve that then
3:13
is easy to achieve that then
3:13
is easy to achieve that then demonstrable ROI and efficiency as well
3:16
demonstrable ROI and efficiency as well
3:16
demonstrable ROI and efficiency as well right so so basically uh this will also
3:18
right so so basically uh this will also
3:18
right so so basically uh this will also improve the speed and quality and cost
3:21
improve the speed and quality and cost
3:21
improve the speed and quality and cost savings as well for if we are going this
3:25
savings as well for if we are going this
3:25
savings as well for if we are going this you know for the long term as such plan
3:27
you know for the long term as such plan
3:27
you know for the long term as such plan for the long term So as we know you know
3:29
for the long term So as we know you know
3:29
for the long term So as we know you know AI is a future and cloud plus AI is
3:33
AI is a future and cloud plus AI is
3:33
AI is a future and cloud plus AI is deadly combination I will say and I'm
3:36
deadly combination I will say and I'm
3:36
deadly combination I will say and I'm also into you know mobile automation and
3:38
also into you know mobile automation and
3:38
also into you know mobile automation and things like that so I can understand how
3:40
things like that so I can understand how
3:40
things like that so I can understand how it is really useful.
3:43
it is really useful.
3:43
it is really useful. Now coming back to uh next slide cross
3:46
Now coming back to uh next slide cross
3:46
Now coming back to uh next slide cross industry success metrics here we are
3:48
industry success metrics here we are
3:48
industry success metrics here we are talking about you know defect reduction
3:51
talking about you know defect reduction
3:51
talking about you know defect reduction 58% of uh defect reduction as such uh
3:54
58% of uh defect reduction as such uh
3:54
58% of uh defect reduction as such uh right and you know uh in production uh
3:58
right and you know uh in production uh
3:58
right and you know uh in production uh this results in fewer user complaints
4:00
this results in fewer user complaints
4:00
this results in fewer user complaints and and reduced churns as well right so
4:03
and and reduced churns as well right so
4:04
and and reduced churns as well right so production we will have very less you
4:05
production we will have very less you
4:06
production we will have very less you know user complaints if we are uh using
4:07
know user complaints if we are uh using
4:08
know user complaints if we are uh using this this matrix also shows about 65%
4:11
this this matrix also shows about 65%
4:11
this this matrix also shows about 65% faster releases as
4:13
faster releases as
4:13
faster releases as You know so from weeks to days making
4:16
You know so from weeks to days making
4:16
You know so from weeks to days making companies more agile as such accelerated
4:19
companies more agile as such accelerated
4:19
companies more agile as such accelerated releases cycles through enhance
4:21
releases cycles through enhance
4:21
releases cycles through enhance automation
4:22
automation
4:22
automation we have uh 45% cost savings as such. So
4:27
we have uh 45% cost savings as such. So
4:27
we have uh 45% cost savings as such. So this reduced infrastructure cost with
4:29
this reduced infrastructure cost with
4:29
this reduced infrastructure cost with optimized cloud native device firms. So
4:33
optimized cloud native device firms. So
4:33
optimized cloud native device firms. So thanks to cloudnative testing
4:35
thanks to cloudnative testing
4:35
thanks to cloudnative testing environments uh which are you know
4:37
environments uh which are you know
4:37
environments uh which are you know really helpful to achieve this uh
4:39
really helpful to achieve this uh
4:40
really helpful to achieve this uh costsaving. Then I will say 99.7%
4:43
costsaving. Then I will say 99.7%
4:43
costsaving. Then I will say 99.7% feature parity achieves crossplatform
4:46
feature parity achieves crossplatform
4:46
feature parity achieves crossplatform consistency via automated validation. Uh
4:50
consistency via automated validation. Uh
4:50
consistency via automated validation. Uh this will ensure you know consistent
4:52
this will ensure you know consistent
4:52
this will ensure you know consistent user experience across the platforms and
4:56
user experience across the platforms and
4:56
user experience across the platforms and this presents powerful success metrics
4:58
this presents powerful success metrics
4:58
this presents powerful success metrics you know from around 500 plus employees.
5:02
you know from around 500 plus employees.
5:02
you know from around 500 plus employees. So yeah this will really help mattress
5:05
So yeah this will really help mattress
5:05
So yeah this will really help mattress and then uh these numbers are not
5:07
and then uh these numbers are not
5:07
and then uh these numbers are not exponential but uh they are proven and
5:10
exponential but uh they are proven and
5:10
exponential but uh they are proven and repeatable always always most of the
5:12
repeatable always always most of the
5:12
repeatable always always most of the times. Now let's move on to next slide
5:16
times. Now let's move on to next slide
5:16
times. Now let's move on to next slide AIdriven predictive testing. So in this
5:19
AIdriven predictive testing. So in this
5:19
AIdriven predictive testing. So in this basically uh purpose of this is
5:22
basically uh purpose of this is
5:22
basically uh purpose of this is basically to explain how AI proactively
5:24
basically to explain how AI proactively
5:24
basically to explain how AI proactively improve the quality how you know
5:27
improve the quality how you know
5:27
improve the quality how you know AIdriven frameworks improves the quality
5:29
AIdriven frameworks improves the quality
5:29
AIdriven frameworks improves the quality uh using cloud-based automation. So
5:32
uh using cloud-based automation. So
5:32
uh using cloud-based automation. So first uh in in this first we have to do
5:34
first uh in in this first we have to do
5:34
first uh in in this first we have to do risk assessment uh uh algorithms are
5:37
risk assessment uh uh algorithms are
5:37
risk assessment uh uh algorithms are there where we are leveraging machine
5:39
there where we are leveraging machine
5:39
there where we are leveraging machine learning algorithms analyze code changes
5:41
learning algorithms analyze code changes
5:41
learning algorithms analyze code changes as such. So this what we are going to do
5:44
as such. So this what we are going to do
5:44
as such. So this what we are going to do is analyze code changes, historical bugs
5:46
is analyze code changes, historical bugs
5:46
is analyze code changes, historical bugs and user behavior to identify high-risk
5:49
and user behavior to identify high-risk
5:49
and user behavior to identify high-risk uh zones. So we are saying why test
5:53
uh zones. So we are saying why test
5:53
uh zones. So we are saying why test everything when AI can tell you what
5:54
everything when AI can tell you what
5:54
everything when AI can tell you what matters the most here right. So
5:57
matters the most here right. So
5:57
matters the most here right. So basically AI will let us know you know
6:01
basically AI will let us know you know
6:01
basically AI will let us know you know this this is the critical part you have
6:03
this this is the critical part you have
6:03
this this is the critical part you have to test more around this. So that is
6:05
to test more around this. So that is
6:05
to test more around this. So that is risk assessment algorithms are there
6:07
risk assessment algorithms are there
6:07
risk assessment algorithms are there with AI models. Uh then we have
6:10
with AI models. Uh then we have
6:10
with AI models. Uh then we have intelligent resource allocation. So uh
6:13
intelligent resource allocation. So uh
6:13
intelligent resource allocation. So uh we have to prioritize our automation uh
6:15
we have to prioritize our automation uh
6:15
we have to prioritize our automation uh basically right so focus testing teams
6:18
basically right so focus testing teams
6:18
basically right so focus testing teams and computer powers on the riskiest most
6:21
and computer powers on the riskiest most
6:21
and computer powers on the riskiest most valuable components. So whatever we
6:23
valuable components. So whatever we
6:23
valuable components. So whatever we seems as a risk we have to you know high
6:25
seems as a risk we have to you know high
6:26
seems as a risk we have to you know high priority task we have to focus more on
6:28
priority task we have to focus more on
6:28
priority task we have to focus more on those and autom automate it uh based on
6:31
those and autom automate it uh based on
6:31
those and autom automate it uh based on the AIdriven uh approaches.
6:34
the AIdriven uh approaches.
6:34
the AIdriven uh approaches. Then we have this proactive defect
6:36
Then we have this proactive defect
6:36
Then we have this proactive defect prevention. So by identifying potential
6:39
prevention. So by identifying potential
6:39
prevention. So by identifying potential issues through pattern recognition early
6:41
issues through pattern recognition early
6:41
issues through pattern recognition early in the development cycle basically. So
6:43
in the development cycle basically. So
6:43
in the development cycle basically. So what we are saying here is catch issues
6:45
what we are saying here is catch issues
6:45
what we are saying here is catch issues before they become uh bugs effectively
6:48
before they become uh bugs effectively
6:48
before they become uh bugs effectively moving quality control earlier in the
6:50
moving quality control earlier in the
6:50
moving quality control earlier in the SDLC life cycle. So that will really
6:54
SDLC life cycle. So that will really
6:54
SDLC life cycle. So that will really help you know uh in uh when we go on
6:57
help you know uh in uh when we go on
6:57
help you know uh in uh when we go on right that will be a cost effective as
7:00
right that will be a cost effective as
7:00
right that will be a cost effective as well if we are identifying is issues
7:02
well if we are identifying is issues
7:02
well if we are identifying is issues upfront using AI and you know this
7:04
upfront using AI and you know this
7:04
upfront using AI and you know this cloud-based platforms.
7:08
cloud-based platforms.
7:08
cloud-based platforms. Now let's talk about industry specific
7:10
Now let's talk about industry specific
7:10
Now let's talk about industry specific success patterns. Uh first we'll talk
7:13
success patterns. Uh first we'll talk
7:13
success patterns. Uh first we'll talk about the financial sources. So purpose
7:16
about the financial sources. So purpose
7:16
about the financial sources. So purpose here is basically tailor AI benefits to
7:18
here is basically tailor AI benefits to
7:18
here is basically tailor AI benefits to specific verticals. So basically based
7:21
specific verticals. So basically based
7:21
specific verticals. So basically based on vertical needs right via financial
7:23
on vertical needs right via financial
7:23
on vertical needs right via financial service retails and healthcare. So
7:25
service retails and healthcare. So
7:25
service retails and healthcare. So financial services if we talk about we
7:27
financial services if we talk about we
7:27
financial services if we talk about we achieved around 43% fewer compliance
7:30
achieved around 43% fewer compliance
7:30
achieved around 43% fewer compliance violations
7:31
violations
7:31
violations and then integrated fraud detection
7:33
and then integrated fraud detection
7:34
and then integrated fraud detection within test automation improved
7:36
within test automation improved
7:36
within test automation improved transaction security uh validation as
7:39
transaction security uh validation as
7:39
transaction security uh validation as such right. So basically uh we are
7:42
such right. So basically uh we are
7:42
such right. So basically uh we are talking about uh like achieved uh
7:45
talking about uh like achieved uh
7:46
talking about uh like achieved uh compliance uh violations and you know
7:49
compliance uh violations and you know
7:49
compliance uh violations and you know integrated fraud detections and uh
7:51
integrated fraud detections and uh
7:51
integrated fraud detections and uh transaction security validations as such
7:53
transaction security validations as such
7:53
transaction security validations as such in financial uh sector. Then if we talk
7:56
in financial uh sector. Then if we talk
7:56
in financial uh sector. Then if we talk about retail
7:58
about retail
7:58
about retail managed uh traffic surges up to 300%
8:01
managed uh traffic surges up to 300%
8:01
managed uh traffic surges up to 300% without failure. So what
8:04
without failure. So what
8:04
without failure. So what we are saying here is you know 300% uh
8:07
we are saying here is you know 300% uh
8:07
we are saying here is you know 300% uh surge we have observed here. Okay. It is
8:09
surge we have observed here. Okay. It is
8:09
surge we have observed here. Okay. It is a managed traffic which enable platform
8:12
a managed traffic which enable platform
8:12
a managed traffic which enable platform to seamlessly handle traffic spikes up
8:14
to seamlessly handle traffic spikes up
8:14
to seamlessly handle traffic spikes up to 300%.
8:16
to 300%.
8:16
to 300%. We we are ensuring checkout process
8:18
We we are ensuring checkout process
8:18
We we are ensuring checkout process resilience under conditions of high
8:20
resilience under conditions of high
8:20
resilience under conditions of high concurrency. So here we are talking
8:22
concurrency. So here we are talking
8:22
concurrency. So here we are talking about you know seamless checkout under
8:25
about you know seamless checkout under
8:25
about you know seamless checkout under various loads. Okay. And then we are
8:28
various loads. Okay. And then we are
8:28
various loads. Okay. And then we are talking about streamlined multi-reion
8:30
talking about streamlined multi-reion
8:30
talking about streamlined multi-reion payment gateway validation for global
8:32
payment gateway validation for global
8:32
payment gateway validation for global reach. Basically uh we are talking about
8:34
reach. Basically uh we are talking about
8:34
reach. Basically uh we are talking about enable global commerce with multi-reion
8:37
enable global commerce with multi-reion
8:37
enable global commerce with multi-reion validations.
8:39
validations.
8:39
validations. that will uh uh in retail basically and
8:42
that will uh uh in retail basically and
8:42
that will uh uh in retail basically and then we talk about healthcare uh
8:44
then we talk about healthcare uh
8:44
then we talk about healthcare uh healthcare we have improved regulatory
8:46
healthcare we have improved regulatory
8:46
healthcare we have improved regulatory testing efficiency by 89%.
8:49
testing efficiency by 89%.
8:49
testing efficiency by 89%. Yeah, that's good uh number 89%
8:51
Yeah, that's good uh number 89%
8:51
Yeah, that's good uh number 89% regulatory then automated HIPPA
8:54
regulatory then automated HIPPA
8:54
regulatory then automated HIPPA compliance basically HIPPA compliance
8:56
compliance basically HIPPA compliance
8:56
compliance basically HIPPA compliance and developed robust uh patient data
8:59
and developed robust uh patient data
8:59
and developed robust uh patient data security validation framework. So
9:00
security validation framework. So
9:00
security validation framework. So standard data privacy uh testing for
9:03
standard data privacy uh testing for
9:03
standard data privacy uh testing for patient records. So yeah, so this AI
9:07
patient records. So yeah, so this AI
9:07
patient records. So yeah, so this AI automation cloud tools you know
9:09
automation cloud tools you know
9:09
automation cloud tools you know basically we are talking about uh it it
9:11
basically we are talking about uh it it
9:11
basically we are talking about uh it it will give you more secured environment
9:14
will give you more secured environment
9:14
will give you more secured environment for all the privacy needs as such for
9:17
for all the privacy needs as such for
9:17
for all the privacy needs as such for all the industries like financial,
9:18
all the industries like financial,
9:18
all the industries like financial, retail and healthcare. So now let's uh
9:21
retail and healthcare. So now let's uh
9:21
retail and healthcare. So now let's uh move on to next slide.
9:23
move on to next slide.
9:24
move on to next slide. So now we are talking about next
9:26
So now we are talking about next
9:26
So now we are talking about next generation automation frameworks right.
9:28
generation automation frameworks right.
9:28
generation automation frameworks right. So we have uh like we have mobile device
9:31
So we have uh like we have mobile device
9:31
So we have uh like we have mobile device forms right uh basically these are
9:34
forms right uh basically these are
9:34
forms right uh basically these are various tools uh that enable
9:36
various tools uh that enable
9:36
various tools uh that enable transformation so cloud native device
9:39
transformation so cloud native device
9:39
transformation so cloud native device forms right so leverage leverage
9:41
forms right so leverage leverage
9:41
forms right so leverage leverage scalable infrastructure for thousands of
9:43
scalable infrastructure for thousands of
9:43
scalable infrastructure for thousands of devices configuration achieve 45% lower
9:45
devices configuration achieve 45% lower
9:45
devices configuration achieve 45% lower cost so what we are saying is
9:48
cost so what we are saying is
9:48
cost so what we are saying is we have various clouds available in the
9:50
we have various clouds available in the
9:50
we have various clouds available in the market like AWS Azure or Amazon device
9:54
market like AWS Azure or Amazon device
9:54
market like AWS Azure or Amazon device farm or there are many others right so
9:57
farm or there are many others right so
9:57
farm or there are many others right so we have in-house house clouds or you
9:59
we have in-house house clouds or you
9:59
we have in-house house clouds or you know uh we have various on-remise clouds
10:03
know uh we have various on-remise clouds
10:03
know uh we have various on-remise clouds as well. So what we are saying is on
10:05
as well. So what we are saying is on
10:05
as well. So what we are saying is on demand scalable and costefficient
10:07
demand scalable and costefficient
10:07
demand scalable and costefficient testing infrastructure as per our needs
10:09
testing infrastructure as per our needs
10:10
testing infrastructure as per our needs right company needs right so uh we can
10:12
right company needs right so uh we can
10:12
right company needs right so uh we can uh leverage that then supports thousands
10:14
uh leverage that then supports thousands
10:14
uh leverage that then supports thousands of devices you know as it we can these
10:18
of devices you know as it we can these
10:18
of devices you know as it we can these are on demand devices we can use any
10:19
are on demand devices we can use any
10:20
are on demand devices we can use any devices right iOS iPads Android devices
10:23
devices right iOS iPads Android devices
10:23
devices right iOS iPads Android devices because it's really not feasible to
10:25
because it's really not feasible to
10:25
because it's really not feasible to purchase all these devices a better
10:27
purchase all these devices a better
10:27
purchase all these devices a better solution is go by cloud with AI and then
10:31
solution is go by cloud with AI and then
10:31
solution is go by cloud with AI and then we can talk about devops integration
10:33
we can talk about devops integration
10:33
we can talk about devops integration pipeline lines. So, integrate seamlessly
10:35
pipeline lines. So, integrate seamlessly
10:35
pipeline lines. So, integrate seamlessly with CIC CD and featuring automated
10:38
with CIC CD and featuring automated
10:38
with CIC CD and featuring automated quality gates and real-time feedback
10:40
quality gates and real-time feedback
10:40
quality gates and real-time feedback loops. Testing becomes part of CI/CD
10:42
loops. Testing becomes part of CI/CD
10:42
loops. Testing becomes part of CI/CD life cycle. Without CI/CD um uh in my uh
10:46
life cycle. Without CI/CD um uh in my uh
10:46
life cycle. Without CI/CD um uh in my uh career nowadays, I have not seen
10:48
career nowadays, I have not seen
10:48
career nowadays, I have not seen anything you know without CI/CD
10:50
anything you know without CI/CD
10:50
anything you know without CI/CD pipelines where we have you know builds
10:52
pipelines where we have you know builds
10:52
pipelines where we have you know builds are getting installed uh scripts are
10:54
are getting installed uh scripts are
10:54
are getting installed uh scripts are getting executed automatically. We are
10:56
getting executed automatically. We are
10:56
getting executed automatically. We are getting the results automatically in no
10:58
getting the results automatically in no
10:58
getting the results automatically in no time. Automated quality gates prevent
11:00
time. Automated quality gates prevent
11:00
time. Automated quality gates prevent bad code from progressing as well. So
11:03
bad code from progressing as well. So
11:03
bad code from progressing as well. So basically using this DevOps integrated
11:05
basically using this DevOps integrated
11:05
basically using this DevOps integrated we can obviously you know u uh quality
11:08
we can obviously you know u uh quality
11:08
we can obviously you know u uh quality gates and realtime feedback loops are
11:10
gates and realtime feedback loops are
11:10
gates and realtime feedback loops are available then crossplatform consistency
11:12
available then crossplatform consistency
11:12
available then crossplatform consistency engine. So utilize unified test suits to
11:15
engine. So utilize unified test suits to
11:15
engine. So utilize unified test suits to ensure 99.7 feature parity across iOS
11:18
ensure 99.7 feature parity across iOS
11:18
ensure 99.7 feature parity across iOS Android web platforms. So what this
11:21
Android web platforms. So what this
11:21
Android web platforms. So what this means is one test suit for Android iOS
11:24
means is one test suit for Android iOS
11:24
means is one test suit for Android iOS and web uh ensures uh 99.7 feature
11:27
and web uh ensures uh 99.7 feature
11:27
and web uh ensures uh 99.7 feature parity. So basically here we are talking
11:30
parity. So basically here we are talking
11:30
parity. So basically here we are talking about synergy components work uh
11:33
about synergy components work uh
11:33
about synergy components work uh together basically all right I mean uh
11:36
together basically all right I mean uh
11:36
together basically all right I mean uh if I am executing one script on iOS or
11:39
if I am executing one script on iOS or
11:39
if I am executing one script on iOS or Android uh and web platforms it will
11:41
Android uh and web platforms it will
11:41
Android uh and web platforms it will work same uh across I don't have to you
11:43
work same uh across I don't have to you
11:43
work same uh across I don't have to you know create different different scripts
11:45
know create different different scripts
11:45
know create different different scripts or you know test cases accordingly. So
11:48
or you know test cases accordingly. So
11:48
or you know test cases accordingly. So yeah this is really a good uh you know
11:51
yeah this is really a good uh you know
11:51
yeah this is really a good uh you know uh framework to use these are all next
11:53
uh framework to use these are all next
11:53
uh framework to use these are all next generation frameworks. Let now let's
11:55
generation frameworks. Let now let's
11:55
generation frameworks. Let now let's move on to next slide.
11:57
move on to next slide.
11:57
move on to next slide. advanc test advanced testing
11:59
advanc test advanced testing
11:59
advanc test advanced testing capabilities basically. So what we are
12:02
capabilities basically. So what we are
12:02
capabilities basically. So what we are trying to show here is uh AI's
12:05
trying to show here is uh AI's
12:05
trying to show here is uh AI's versatility in handling modern
12:06
versatility in handling modern
12:06
versatility in handling modern challenges. So real time fraud detection
12:09
challenges. So real time fraud detection
12:10
challenges. So real time fraud detection integrated advanced fraud detection
12:11
integrated advanced fraud detection
12:11
integrated advanced fraud detection algorithms directly into testing
12:13
algorithms directly into testing
12:13
algorithms directly into testing workflows ensuring robust security
12:15
workflows ensuring robust security
12:15
workflows ensuring robust security validation before deployment. So what we
12:17
validation before deployment. So what we
12:17
validation before deployment. So what we are trying to say here is test actively
12:20
are trying to say here is test actively
12:20
are trying to say here is test actively simulate fraud scenarios to validate
12:22
simulate fraud scenarios to validate
12:22
simulate fraud scenarios to validate defenses basically right. So basically
12:25
defenses basically right. So basically
12:25
defenses basically right. So basically uh we are trying to execute fraud
12:28
uh we are trying to execute fraud
12:28
uh we are trying to execute fraud scenarios uh which will validate uh our
12:30
scenarios uh which will validate uh our
12:30
scenarios uh which will validate uh our defenses as such right. Then we are
12:32
defenses as such right. Then we are
12:32
defenses as such right. Then we are talking about global language
12:34
talking about global language
12:34
talking about global language validation. So auto automate testing
12:37
validation. So auto automate testing
12:37
validation. So auto automate testing across 40 plus markets and language
12:38
across 40 plus markets and language
12:38
across 40 plus markets and language guaranting consistent localized user
12:41
guaranting consistent localized user
12:41
guaranting consistent localized user experience worldwide.
12:43
experience worldwide.
12:43
experience worldwide. So what we are trying to say here is uh
12:45
So what we are trying to say here is uh
12:46
So what we are trying to say here is uh we have 40 plus markets to ensure
12:48
we have 40 plus markets to ensure
12:48
we have 40 plus markets to ensure localization. There are many languages
12:50
localization. There are many languages
12:50
localization. There are many languages many markets are available right. So
12:52
many markets are available right. So
12:52
many markets are available right. So yeah it's available in all uh different
12:55
yeah it's available in all uh different
12:55
yeah it's available in all uh different languages wherever you know we have a
12:57
languages wherever you know we have a
12:57
languages wherever you know we have a reach. So global language validation
12:59
reach. So global language validation
12:59
reach. So global language validation then we have comprehensive network
13:01
then we have comprehensive network
13:01
then we have comprehensive network simulation. So conduct precise
13:03
simulation. So conduct precise
13:03
simulation. So conduct precise performance testing under device uh
13:05
performance testing under device uh
13:05
performance testing under device uh diverse connectivity scenarios from high
13:07
diverse connectivity scenarios from high
13:07
diverse connectivity scenarios from high speeded 5G to intermittent rural
13:10
speeded 5G to intermittent rural
13:10
speeded 5G to intermittent rural connections. So what we are trying to
13:11
connections. So what we are trying to
13:11
connections. So what we are trying to say here is test simulate 5G 4G 3G or
13:15
say here is test simulate 5G 4G 3G or
13:15
say here is test simulate 5G 4G 3G or any unstable connections where we don't
13:17
any unstable connections where we don't
13:17
any unstable connections where we don't have much network. It's vital for
13:19
have much network. It's vital for
13:19
have much network. It's vital for ensuring you know our mobile net apps
13:21
ensuring you know our mobile net apps
13:21
ensuring you know our mobile net apps work well in rural or emerging markets
13:24
work well in rural or emerging markets
13:24
work well in rural or emerging markets as such. So yeah we uh this AI uh driven
13:29
as such. So yeah we uh this AI uh driven
13:29
as such. So yeah we uh this AI uh driven you know networking capabilities are
13:30
you know networking capabilities are
13:30
you know networking capabilities are there you know which will help on in uh
13:33
there you know which will help on in uh
13:33
there you know which will help on in uh all these you know networks areas as
13:35
all these you know networks areas as
13:35
all these you know networks areas as well. Then we have automated
13:37
well. Then we have automated
13:37
well. Then we have automated accessibility compliance where we are
13:39
accessibility compliance where we are
13:40
accessibility compliance where we are leveraging AI powered uh visual
13:42
leveraging AI powered uh visual
13:42
leveraging AI powered uh visual recognition to automatically validate
13:44
recognition to automatically validate
13:44
recognition to automatically validate the adherence to WCAG 2.1 standards
13:47
the adherence to WCAG 2.1 standards
13:47
the adherence to WCAG 2.1 standards enhancing inclusivity. So what we are
13:50
enhancing inclusivity. So what we are
13:50
enhancing inclusivity. So what we are trying to say here is uh visual AI
13:52
trying to say here is uh visual AI
13:52
trying to say here is uh visual AI checks and apps against WCAG 2.1
13:55
checks and apps against WCAG 2.1
13:55
checks and apps against WCAG 2.1 standards promotes inclusivity and
13:58
standards promotes inclusivity and
13:58
standards promotes inclusivity and compliance with global regulations
14:00
compliance with global regulations
14:00
compliance with global regulations basically. Yeah. So this uh so these
14:04
basically. Yeah. So this uh so these
14:04
basically. Yeah. So this uh so these cutting edge capabilities collectively
14:06
cutting edge capabilities collectively
14:06
cutting edge capabilities collectively provide uh you know unparallel testing
14:09
provide uh you know unparallel testing
14:09
provide uh you know unparallel testing coverage efficiency for surpassing the
14:11
coverage efficiency for surpassing the
14:11
coverage efficiency for surpassing the limitation of traditional approaches.
14:13
limitation of traditional approaches.
14:13
limitation of traditional approaches. Yes, nowadays this is really helping
14:16
Yes, nowadays this is really helping
14:16
Yes, nowadays this is really helping cloud plus AI.
14:18
cloud plus AI.
14:18
cloud plus AI. Okay. So now let's move on to I think um
14:22
Okay. So now let's move on to I think um
14:22
Okay. So now let's move on to I think um there's a case study global financial
14:24
there's a case study global financial
14:24
there's a case study global financial institution. uh so over here you know I
14:27
institution. uh so over here you know I
14:27
institution. uh so over here you know I would like to talk on these challenges
14:30
would like to talk on these challenges
14:30
would like to talk on these challenges what uh we have in traditional manual
14:32
what uh we have in traditional manual
14:32
what uh we have in traditional manual approaches basically global financial
14:34
approaches basically global financial
14:34
approaches basically global financial institution case study so we have around
14:37
institution case study so we have around
14:37
institution case study so we have around 2,000 manual test cases lengy 8 weeks
14:40
2,000 manual test cases lengy 8 weeks
14:40
2,000 manual test cases lengy 8 weeks regression cycles persistent compliance
14:42
regression cycles persistent compliance
14:42
regression cycles persistent compliance issues uh recurrent critical production
14:45
issues uh recurrent critical production
14:45
issues uh recurrent critical production defects as such right so always you know
14:48
defects as such right so always you know
14:48
defects as such right so always you know in traditional ways we are having a lot
14:50
in traditional ways we are having a lot
14:50
in traditional ways we are having a lot of challenges you know uh I don't have
14:52
of challenges you know uh I don't have
14:52
of challenges you know uh I don't have to go much detail into it but yeah as uh
14:55
to go much detail into it but yeah as uh
14:55
to go much detail into it but yeah as uh manual QA how we are going to do uh but
14:58
manual QA how we are going to do uh but
14:58
manual QA how we are going to do uh but uh now we will see how AI powered
15:00
uh now we will see how AI powered
15:00
uh now we will see how AI powered solution will you know help us here. So
15:03
solution will you know help us here. So
15:03
solution will you know help us here. So implemented predictive test
15:04
implemented predictive test
15:04
implemented predictive test prioritization. So here what we are
15:07
prioritization. So here what we are
15:07
prioritization. So here what we are talking about is predictive
15:09
talking about is predictive
15:09
talking about is predictive prioritization streamline testing
15:11
prioritization streamline testing
15:11
prioritization streamline testing basically we know you know this might
15:13
basically we know you know this might
15:13
basically we know you know this might happen using AI powered solutions right
15:16
happen using AI powered solutions right
15:16
happen using AI powered solutions right AI knows okay this is going to happen if
15:18
AI knows okay this is going to happen if
15:18
AI knows okay this is going to happen if we are going to use this then deployed a
15:20
we are going to use this then deployed a
15:20
we are going to use this then deployed a cloudnative device form. So we are
15:23
cloudnative device form. So we are
15:23
cloudnative device form. So we are having cloud native device forms
15:25
having cloud native device forms
15:25
having cloud native device forms expanded coverage. So we have thousands
15:27
expanded coverage. So we have thousands
15:27
expanded coverage. So we have thousands of devices in iOS and Android now you
15:29
of devices in iOS and Android now you
15:30
of devices in iOS and Android now you know and then establish automated uh
15:32
know and then establish automated uh
15:32
know and then establish automated uh compliance validation. Automated
15:34
compliance validation. Automated
15:34
compliance validation. Automated compliance test uh eliminates manual
15:36
compliance test uh eliminates manual
15:36
compliance test uh eliminates manual checks. So uh right now if we are doing
15:39
checks. So uh right now if we are doing
15:39
checks. So uh right now if we are doing any manual challenges in this case study
15:41
any manual challenges in this case study
15:41
any manual challenges in this case study what we are showing is you know if we
15:42
what we are showing is you know if we
15:42
what we are showing is you know if we are automated compliance validations
15:44
are automated compliance validations
15:44
are automated compliance validations that will eliminate manual intervention
15:47
that will eliminate manual intervention
15:47
that will eliminate manual intervention adopted a comprehensive risk based
15:49
adopted a comprehensive risk based
15:49
adopted a comprehensive risk based testing framework as such right so now
15:52
testing framework as such right so now
15:52
testing framework as such right so now we are talking results we uh achieved
15:54
we are talking results we uh achieved
15:54
we are talking results we uh achieved around 94% automation coverage reduced
15:57
around 94% automation coverage reduced
15:57
around 94% automation coverage reduced regulation cycle from weeks to days yes
16:00
regulation cycle from weeks to days yes
16:00
regulation cycle from weeks to days yes this is really great I mean if we have
16:02
this is really great I mean if we have
16:02
this is really great I mean if we have you know eliminated all compliance
16:04
you know eliminated all compliance
16:04
you know eliminated all compliance violations yes compliance Violations are
16:07
violations yes compliance Violations are
16:07
violations yes compliance Violations are once automated. Until there are changes,
16:10
once automated. Until there are changes,
16:10
once automated. Until there are changes, you don't have to worry about it. But if
16:12
you don't have to worry about it. But if
16:12
you don't have to worry about it. But if you're doing it manually, obviously
16:14
you're doing it manually, obviously
16:14
you're doing it manually, obviously there is a chance you might fail again.
16:17
there is a chance you might fail again.
16:17
there is a chance you might fail again. Relies, you know, uh this uh 387%
16:20
Relies, you know, uh this uh 387%
16:20
Relies, you know, uh this uh 387% of uh return of year. So yeah, it's a
16:23
of uh return of year. So yeah, it's a
16:23
of uh return of year. So yeah, it's a good uh uh return of investment over the
16:27
good uh uh return of investment over the
16:27
good uh uh return of investment over the uh period of you know time in year first
16:30
uh period of you know time in year first
16:30
uh period of you know time in year first year and this is going to improve more
16:32
year and this is going to improve more
16:32
year and this is going to improve more and more in you know coming years as
16:34
and more in you know coming years as
16:34
and more in you know coming years as such. Okay, now let's move on to next
16:37
such. Okay, now let's move on to next
16:37
such. Okay, now let's move on to next slide implementation road map. So here
16:41
slide implementation road map. So here
16:41
slide implementation road map. So here we are talking about you know giving a
16:43
we are talking about you know giving a
16:43
we are talking about you know giving a clear step-by-step transformation
16:45
clear step-by-step transformation
16:45
clear step-by-step transformation strategy. So first phase is assessment
16:47
strategy. So first phase is assessment
16:47
strategy. So first phase is assessment phase. So here what we are talking about
16:49
phase. So here what we are talking about
16:50
phase. So here what we are talking about uh evaluate current testing maturity to
16:52
uh evaluate current testing maturity to
16:52
uh evaluate current testing maturity to identify high impact automation
16:53
identify high impact automation
16:53
identify high impact automation opportunities.
16:55
opportunities.
16:55
opportunities. Okay. So we are talking about you know
16:57
Okay. So we are talking about you know
16:57
Okay. So we are talking about you know analyze current process, identify impact
16:59
analyze current process, identify impact
16:59
analyze current process, identify impact automation areas, estimate ROI
17:01
automation areas, estimate ROI
17:01
automation areas, estimate ROI calculations as such. Then we are
17:03
calculations as such. Then we are
17:03
calculations as such. Then we are talking about foundation building.
17:05
talking about foundation building.
17:05
talking about foundation building. Second step estab establish uh establish
17:08
Second step estab establish uh establish
17:08
Second step estab establish uh establish foundation infrastructure and
17:10
foundation infrastructure and
17:10
foundation infrastructure and frameworks. So basically we are talking
17:12
frameworks. So basically we are talking
17:12
frameworks. So basically we are talking about here setup cloud devices
17:14
about here setup cloud devices
17:14
about here setup cloud devices integrated with CI/CD pipelines and then
17:16
integrated with CI/CD pipelines and then
17:16
integrated with CI/CD pipelines and then ensure strong data test data practices
17:18
ensure strong data test data practices
17:18
ensure strong data test data practices are followed. So yeah this is a
17:21
are followed. So yeah this is a
17:21
are followed. So yeah this is a foundation uh block uh for this. Then we
17:24
foundation uh block uh for this. Then we
17:24
foundation uh block uh for this. Then we are talking about AI integration. So we
17:26
are talking about AI integration. So we
17:26
are talking about AI integration. So we are talking about add predictive testing
17:28
are talking about add predictive testing
17:28
are talking about add predictive testing use self-healing scripts then deploy
17:31
use self-healing scripts then deploy
17:31
use self-healing scripts then deploy visual AI or for UI checks basically. So
17:36
visual AI or for UI checks basically. So
17:36
visual AI or for UI checks basically. So yeah so we are talking about you know
17:37
yeah so we are talking about you know
17:37
yeah so we are talking about you know predictive models self-filling visual uh
17:40
predictive models self-filling visual uh
17:40
predictive models self-filling visual uh data validations as such then we'll talk
17:42
data validations as such then we'll talk
17:42
data validations as such then we'll talk about scale and optimize
17:45
about scale and optimize
17:45
about scale and optimize expanding test coverage refined
17:46
expanding test coverage refined
17:46
expanding test coverage refined frameworks right expand coverage and
17:48
frameworks right expand coverage and
17:48
frameworks right expand coverage and scope refine for performance and
17:50
scope refine for performance and
17:50
scope refine for performance and continuous improvement yes whatever uh
17:53
continuous improvement yes whatever uh
17:53
continuous improvement yes whatever uh technology uh we are using right whether
17:56
technology uh we are using right whether
17:56
technology uh we are using right whether it's AI cloud or in future also whatever
17:59
it's AI cloud or in future also whatever
17:59
it's AI cloud or in future also whatever is there every technology needs a
18:01
is there every technology needs a
18:02
is there every technology needs a continuous you know performance
18:03
continuous you know performance
18:03
continuous you know performance optimization or continuous improvement
18:05
optimization or continuous improvement
18:05
optimization or continuous improvement is required. Okay, this is iterative
18:08
is required. Okay, this is iterative
18:08
is required. Okay, this is iterative process. It's not one sizefits all. So
18:11
process. It's not one sizefits all. So
18:11
process. It's not one sizefits all. So basically we have to customize it also
18:13
basically we have to customize it also
18:13
basically we have to customize it also as per the needs. Okay, so now let's
18:16
as per the needs. Okay, so now let's
18:16
as per the needs. Okay, so now let's move on to next slide. High performance
18:19
move on to next slide. High performance
18:19
move on to next slide. High performance techniques. Okay. So we will talk about
18:22
techniques. Okay. So we will talk about
18:22
techniques. Okay. So we will talk about some high performance uh techniques
18:24
some high performance uh techniques
18:24
some high performance uh techniques here. Purpose here is share the habits
18:26
here. Purpose here is share the habits
18:26
here. Purpose here is share the habits of top performing organizations
18:28
of top performing organizations
18:28
of top performing organizations basically. So shift left quality culture
18:32
basically. So shift left quality culture
18:32
basically. So shift left quality culture we are talking about here. QA starts at
18:34
we are talking about here. QA starts at
18:34
we are talking about here. QA starts at the design and development stage right
18:36
the design and development stage right
18:36
the design and development stage right so integrate testing through the entire
18:38
so integrate testing through the entire
18:38
so integrate testing through the entire development cycle rather than a final
18:40
development cycle rather than a final
18:40
development cycle rather than a final gate cuts defects remediation cost up to
18:43
gate cuts defects remediation cost up to
18:44
gate cuts defects remediation cost up to you know uh 67%.
18:46
you know uh 67%.
18:46
you know uh 67%. So we have to involve uh in quality
18:50
So we have to involve uh in quality
18:50
So we have to involve uh in quality gates using AI basically or clouds and
18:53
gates using AI basically or clouds and
18:53
gates using AI basically or clouds and AI from the beginning itself. We should
18:56
AI from the beginning itself. We should
18:56
AI from the beginning itself. We should not wait till and end you know once it's
18:58
not wait till and end you know once it's
18:58
not wait till and end you know once it's developed then we are going to do it. So
19:00
developed then we are going to do it. So
19:00
developed then we are going to do it. So we have to always shift left then
19:02
we have to always shift left then
19:02
we have to always shift left then continuous learning models implement AI
19:05
continuous learning models implement AI
19:05
continuous learning models implement AI system that analyze test results adapt
19:07
system that analyze test results adapt
19:07
system that analyze test results adapt continuously. So what we are talking
19:09
continuously. So what we are talking
19:09
continuously. So what we are talking about here is AI system evolves with
19:11
about here is AI system evolves with
19:11
about here is AI system evolves with every test runs self-improving
19:14
every test runs self-improving
19:14
every test runs self-improving algorithms deliver smarter coverage. So
19:16
algorithms deliver smarter coverage. So
19:16
algorithms deliver smarter coverage. So basically yes uh so as and when you know
19:19
basically yes uh so as and when you know
19:19
basically yes uh so as and when you know your model is matured obviously you have
19:21
your model is matured obviously you have
19:21
your model is matured obviously you have to keep on learning your models again
19:23
to keep on learning your models again
19:23
to keep on learning your models again and again AI models as and when you
19:26
and again AI models as and when you
19:26
and again AI models as and when you learn more it will be you know more
19:29
learn more it will be you know more
19:29
learn more it will be you know more stable as such but yes this learning
19:31
stable as such but yes this learning
19:32
stable as such but yes this learning process should continues always then
19:34
process should continues always then
19:34
process should continues always then cross functional ownership we are
19:35
cross functional ownership we are
19:35
cross functional ownership we are talking about establish share quality
19:37
talking about establish share quality
19:37
talking about establish share quality metrics across development QA operations
19:40
metrics across development QA operations
19:40
metrics across development QA operations so we are talking about quality is
19:41
so we are talking about quality is
19:41
so we are talking about quality is everyone's responsibility here basically
19:44
everyone's responsibility here basically
19:44
everyone's responsibility here basically you know developer QA for ops team
19:46
you know developer QA for ops team
19:46
you know developer QA for ops team unified matrix create alignment and
19:48
unified matrix create alignment and
19:48
unified matrix create alignment and accountability as such. So basically
19:50
accountability as such. So basically
19:50
accountability as such. So basically everybody as a team has to work from
19:52
everybody as a team has to work from
19:52
everybody as a team has to work from start to end. It's not only QA job not
19:55
start to end. It's not only QA job not
19:55
start to end. It's not only QA job not only dev job you know not only operation
19:58
only dev job you know not only operation
19:58
only dev job you know not only operation job collectively uh we will make uh you
20:01
job collectively uh we will make uh you
20:01
job collectively uh we will make uh you know a good product using AI.
20:05
know a good product using AI.
20:05
know a good product using AI. Next is key takeaways and next steps.
20:09
Next is key takeaways and next steps.
20:09
Next is key takeaways and next steps. So we'll summarize value and prompt
20:12
So we'll summarize value and prompt
20:12
So we'll summarize value and prompt action around this. Basically strategic
20:14
action around this. Basically strategic
20:14
action around this. Basically strategic insights AI powered testing delivers
20:18
insights AI powered testing delivers
20:18
insights AI powered testing delivers measurable ROI across industries.
20:21
measurable ROI across industries.
20:21
measurable ROI across industries. Predictive models enable proactive
20:23
Predictive models enable proactive
20:23
Predictive models enable proactive quality management. So here we are
20:25
quality management. So here we are
20:25
quality management. So here we are talking about AI testing deliver
20:26
talking about AI testing deliver
20:26
talking about AI testing deliver measurable uh results. Predictive model
20:30
measurable uh results. Predictive model
20:30
measurable uh results. Predictive model reduce rework and waste and then
20:32
reduce rework and waste and then
20:32
reduce rework and waste and then industry specific patterns accelate
20:34
industry specific patterns accelate
20:34
industry specific patterns accelate transformation. Basically what we are
20:36
transformation. Basically what we are
20:36
transformation. Basically what we are saying is industry uses cases prove
20:39
saying is industry uses cases prove
20:39
saying is industry uses cases prove viability. Then we are talking about
20:41
viability. Then we are talking about
20:41
viability. Then we are talking about high performance achieve 78% you know
20:43
high performance achieve 78% you know
20:43
high performance achieve 78% you know greater automation maturity. So so
20:46
greater automation maturity. So so
20:46
greater automation maturity. So so basically we are talking about leaders
20:47
basically we are talking about leaders
20:47
basically we are talking about leaders gain 78% high automation maturity here.
20:51
gain 78% high automation maturity here.
20:51
gain 78% high automation maturity here. So action plans basically what we can do
20:53
So action plans basically what we can do
20:54
So action plans basically what we can do assess current testing maturity. Okay.
20:56
assess current testing maturity. Okay.
20:56
assess current testing maturity. Okay. So what is going on currently? We can
20:58
So what is going on currently? We can
20:58
So what is going on currently? We can assess it. Identify automation
21:00
assess it. Identify automation
21:00
assess it. Identify automation opportunities. We should always try to
21:02
opportunities. We should always try to
21:02
opportunities. We should always try to identify opportunities which is critical
21:05
identify opportunities which is critical
21:05
identify opportunities which is critical and repeatable most of the time. Then we
21:08
and repeatable most of the time. Then we
21:08
and repeatable most of the time. Then we can evaluate cloud device farm
21:10
can evaluate cloud device farm
21:10
can evaluate cloud device farm solutions. Okay. Obviously we should uh
21:13
solutions. Okay. Obviously we should uh
21:13
solutions. Okay. Obviously we should uh know which cloud solution is better for
21:15
know which cloud solution is better for
21:15
know which cloud solution is better for us. Basically in-house on premise or
21:18
us. Basically in-house on premise or
21:18
us. Basically in-house on premise or cloud-based solutions. Uh we want in
21:21
cloud-based solutions. Uh we want in
21:21
cloud-based solutions. Uh we want in private network, public network, we have
21:24
private network, public network, we have
21:24
private network, public network, we have various uh cloud vendors available. We
21:26
various uh cloud vendors available. We
21:26
various uh cloud vendors available. We can use leverage those right. uh then
21:29
can use leverage those right. uh then
21:29
can use leverage those right. uh then pilot AI testing in a critical workflow,
21:31
pilot AI testing in a critical workflow,
21:31
pilot AI testing in a critical workflow, pilot predictive testing. Basically what
21:33
pilot predictive testing. Basically what
21:33
pilot predictive testing. Basically what we are saying is we should have a uh uh
21:36
we are saying is we should have a uh uh
21:36
we are saying is we should have a uh uh you know pilot testing in a critical uh
21:39
you know pilot testing in a critical uh
21:39
you know pilot testing in a critical uh workflow as such. So basically we should
21:42
workflow as such. So basically we should
21:42
workflow as such. So basically we should create some pilot or demo sort of thing
21:44
create some pilot or demo sort of thing
21:44
create some pilot or demo sort of thing for that you know critical workflow
21:47
for that you know critical workflow
21:47
for that you know critical workflow before you know automating all
21:49
before you know automating all
21:49
before you know automating all everything and track and communicate
21:52
everything and track and communicate
21:52
everything and track and communicate wins early. So measure and communicate
21:54
wins early. So measure and communicate
21:54
wins early. So measure and communicate basically we have to make sure tracking
21:56
basically we have to make sure tracking
21:56
basically we have to make sure tracking and communication is good so that you
21:58
and communication is good so that you
21:58
and communication is good so that you know uh we should uh uh achieve our goal
22:02
know uh we should uh uh achieve our goal
22:02
know uh we should uh uh achieve our goal in a good way basically. So uh okay so
22:07
in a good way basically. So uh okay so
22:07
in a good way basically. So uh okay so let's talk about where and how we can
22:09
let's talk about where and how we can
22:10
let's talk about where and how we can help basically so yeah u QA leaders who
22:14
help basically so yeah u QA leaders who
22:14
help basically so yeah u QA leaders who should follow basically QA leaders
22:16
should follow basically QA leaders
22:16
should follow basically QA leaders mobile automation devops technology
22:18
mobile automation devops technology
22:18
mobile automation devops technology executives focus on scaling quality and
22:20
executives focus on scaling quality and
22:20
executives focus on scaling quality and mobile first organization. So yes um so
22:25
mobile first organization. So yes um so
22:25
mobile first organization. So yes um so with that I think we are done. Thank
22:28
with that I think we are done. Thank
22:28
with that I think we are done. Thank you. Thank you.
22:29
you. Thank you.
22:29
you. Thank you. >> That's absolutely great sh around you
22:31
>> That's absolutely great sh around you
22:31
>> That's absolutely great sh around you know the mobile testing. Thank you so
22:33
know the mobile testing. Thank you so
22:33
know the mobile testing. Thank you so much for sharing your pearls of wisdom.
22:35
much for sharing your pearls of wisdom.
22:35
much for sharing your pearls of wisdom. If I may you know what kind of mindset
22:37
If I may you know what kind of mindset
22:37
If I may you know what kind of mindset you know is needed for leaders who are
22:39
you know is needed for leaders who are
22:39
you know is needed for leaders who are still trying you know who still relying
22:41
still trying you know who still relying
22:41
still trying you know who still relying on legacy test automation and want to
22:43
on legacy test automation and want to
22:43
on legacy test automation and want to move to AI you know what kind of mind
22:45
move to AI you know what kind of mind
22:45
move to AI you know what kind of mind shift is needed because the decision
22:47
shift is needed because the decision
22:47
shift is needed because the decision usually comes up from the top.
22:50
usually comes up from the top.
22:50
usually comes up from the top. >> Yes. Yes. So mindset what I will say
22:53
>> Yes. Yes. So mindset what I will say
22:53
>> Yes. Yes. So mindset what I will say just go for it. I mean AI is the future
22:55
just go for it. I mean AI is the future
22:55
just go for it. I mean AI is the future right you cannot uh want to left behind
22:58
right you cannot uh want to left behind
22:58
right you cannot uh want to left behind you know if you are not starting now you
23:01
you know if you are not starting now you
23:01
you know if you are not starting now you will be too late after 2 years or 3
23:03
will be too late after 2 years or 3
23:03
will be too late after 2 years or 3 years that's I that's what I will say
23:05
years that's I that's what I will say
23:05
years that's I that's what I will say because without AI there's no future uh
23:09
because without AI there's no future uh
23:09
because without AI there's no future uh of you know any manual testing or
23:11
of you know any manual testing or
23:11
of you know any manual testing or automation testing okay I know
23:13
automation testing okay I know
23:13
automation testing okay I know automation is going on but we have to
23:17
automation is going on but we have to
23:17
automation is going on but we have to start from today itself so that we can
23:20
start from today itself so that we can
23:20
start from today itself so that we can integrate our AI models as such now if
23:23
integrate our AI models as such now if
23:23
integrate our AI models as such now if you We have AWS, Azure and you know many
23:26
you We have AWS, Azure and you know many
23:26
you We have AWS, Azure and you know many other vendors are there. We are using
23:28
other vendors are there. We are using
23:28
other vendors are there. We are using you know a lot of cloud platforms uh
23:31
you know a lot of cloud platforms uh
23:31
you know a lot of cloud platforms uh like CEST or Amazon device forms
23:33
like CEST or Amazon device forms
23:33
like CEST or Amazon device forms anything they are also leveraging the AI
23:35
anything they are also leveraging the AI
23:35
anything they are also leveraging the AI models. So yes sooner the better. I
23:38
models. So yes sooner the better. I
23:38
models. So yes sooner the better. I think there's no another way out of not
23:42
think there's no another way out of not
23:42
think there's no another way out of not adopting to this AI culture anymore.
23:45
adopting to this AI culture anymore.
23:45
adopting to this AI culture anymore. >> Very well said. Thank you. I'll ask you
23:47
>> Very well said. Thank you. I'll ask you
23:47
>> Very well said. Thank you. I'll ask you one final question before we wrap it up
23:48
one final question before we wrap it up
23:48
one final question before we wrap it up is you know for teams who want to take
23:51
is you know for teams who want to take
23:51
is you know for teams who want to take the next step. I know you did talk about
23:52
the next step. I know you did talk about
23:52
the next step. I know you did talk about some of the cloud tools available right
23:54
some of the cloud tools available right
23:54
some of the cloud tools available right for teams who want to take the next step
23:56
for teams who want to take the next step
23:56
for teams who want to take the next step after this session. What are the some
23:58
after this session. What are the some
23:58
after this session. What are the some resources or platform or best practices
24:00
resources or platform or best practices
24:00
resources or platform or best practices you would recommend? Any place any any
24:02
you would recommend? Any place any any
24:02
you would recommend? Any place any any website that you visit very regularly or
24:05
website that you visit very regularly or
24:05
website that you visit very regularly or any blogs or videos or channels that you
24:07
any blogs or videos or channels that you
24:07
any blogs or videos or channels that you follow?
24:08
follow?
24:08
follow? >> Basically you know we uh in Cognizant we
24:12
>> Basically you know we uh in Cognizant we
24:12
>> Basically you know we uh in Cognizant we have internal blogs we follow that but
24:14
have internal blogs we follow that but
24:14
have internal blogs we follow that but yes apart from that you know AI for AI I
24:18
yes apart from that you know AI for AI I
24:18
yes apart from that you know AI for AI I am also planning for some advanced level
24:20
am also planning for some advanced level
24:20
am also planning for some advanced level certifications. I go to AWS, Azure,
24:23
certifications. I go to AWS, Azure,
24:23
certifications. I go to AWS, Azure, people are doing lot of certifications
24:25
people are doing lot of certifications
24:25
people are doing lot of certifications around it. So if you can you know search
24:27
around it. So if you can you know search
24:27
around it. So if you can you know search on AI Google or AWS certificates or you
24:31
on AI Google or AWS certificates or you
24:31
on AI Google or AWS certificates or you know uh Azure certificates you will find
24:33
know uh Azure certificates you will find
24:33
know uh Azure certificates you will find lot of stuff there and I will suggest
24:36
lot of stuff there and I will suggest
24:36
lot of stuff there and I will suggest that is a key uh if you want to
24:38
that is a key uh if you want to
24:38
that is a key uh if you want to understand AI go for some fundamental
24:41
understand AI go for some fundamental
24:41
understand AI go for some fundamental certifications around it and then you
24:43
certifications around it and then you
24:43
certifications around it and then you will have a I will say not good but yeah
24:46
will have a I will say not good but yeah
24:46
will have a I will say not good but yeah better understanding of you know how to
24:48
better understanding of you know how to
24:48
better understanding of you know how to leverage AI. uh that will really help
24:51
leverage AI. uh that will really help
24:51
leverage AI. uh that will really help the future leaders as well as well as
24:54
the future leaders as well as well as
24:54
the future leaders as well as well as people you know who wants to grow their
24:57
people you know who wants to grow their
24:57
people you know who wants to grow their career in IT fields or any other fields
25:00
career in IT fields or any other fields
25:00
career in IT fields or any other fields AI is not related to IT right so you
25:02
AI is not related to IT right so you
25:02
AI is not related to IT right so you should learn and go for those
25:03
should learn and go for those
25:03
should learn and go for those certifications
25:05
certifications
25:05
certifications >> well thank you so much sir yeah that
25:07
>> well thank you so much sir yeah that
25:07
>> well thank you so much sir yeah that that's very very well answered any final
25:10
that's very very well answered any final
25:10
that's very very well answered any final thing you want to say before we wrap up
25:12
thing you want to say before we wrap up
25:12
thing you want to say before we wrap up this show
25:13
this show
25:13
this show >> I would like to say thank you for giving
25:15
>> I would like to say thank you for giving
25:15
>> I would like to say thank you for giving me this opportunity and u I have lot of
25:18
me this opportunity and u I have lot of
25:18
me this opportunity and u I have lot of other things in future if I'll that
25:20
other things in future if I'll that
25:20
other things in future if I'll that opportunity I would like to you know
25:21
opportunity I would like to you know
25:21
opportunity I would like to you know present uh that as well. So yeah I'm
25:25
present uh that as well. So yeah I'm
25:25
present uh that as well. So yeah I'm working as a leader so I know you know
25:26
working as a leader so I know you know
25:26
working as a leader so I know you know what all things you know we can present
25:28
what all things you know we can present
25:28
what all things you know we can present and you know many people can utilize uh
25:31
and you know many people can utilize uh
25:31
and you know many people can utilize uh that uh things and also I have written
25:34
that uh things and also I have written
25:34
that uh things and also I have written few articles uh they can search via my
25:36
few articles uh they can search via my
25:36
few articles uh they can search via my name and those articles are present on
25:38
name and those articles are present on
25:38
name and those articles are present on you know various websites as such if
25:41
you know various websites as such if
25:41
you know various websites as such if they want to
25:41
they want to
25:41
they want to >> perfect sir thank you so much thank you
25:43
>> perfect sir thank you so much thank you
25:43
>> perfect sir thank you so much thank you so much for your time today and thank
25:44
so much for your time today and thank
25:44
so much for your time today and thank you so much for joining that was it in
25:46
you so much for joining that was it in
25:46
you so much for joining that was it in this episode of a dev tools today and
25:48
this episode of a dev tools today and
25:48
this episode of a dev tools today and we'll see you in some other episode
25:50
we'll see you in some other episode
25:50
we'll see you in some other episode thank you
25:50
thank you
25:50
thank you >> thank you very much good day bye