Latest / Identity at the Center / #395 - Sponsor Spotlight - Redblock

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#395 - Sponsor Spotlight - Redblock · Identity at the Center

0:04
This is identity at the center. Welcome to the Identity of the
0:10
Center podcast. I'm Jeff, and that's Jim.
0:12
Hey, Jim. Hey, Jeff, how are you?
0:14
Not so bad yourself. Fantastic here at the Gartner I
0:16
am Summit 2025 in Grapevine, TX. Yeah, so I refrained from
0:22
mentioning the cowboy hat. I did that already a couple
0:24
times, but here I am mentioning it again.
0:27
Yeah, well, hey, what I'm in Texas do as the Texans do.
0:30
Yeah, so we've got a special 1 today.
0:32
We are doing a sponsored episode with our friends over at Red
0:35
Block. So we're going to get right into
0:37
a second. But you want to learn about Red
0:38
Block? It's Red Block dot AI slash
0:41
IDAC. We'll have links in our show
0:42
notes for people to check out, but let me go ahead and
0:45
introduce your CEO, Indus Kai Tan.
0:46
Welcome to the show. Well a fantastic day at
0:49
Grapevine, TX. It's such a beautiful hotel.
0:51
I I wish my children and my wife was here.
0:54
There are a lot of children and wives here.
0:56
I think people are taking advantage of sort of like
0:57
there's a Christmas kind of festive type holiday thing going
1:00
on here. There's a build-a-bear workshop.
1:02
So other than identity and access management, there are
1:05
things for people to do. Kind of odd place to have a
1:07
conference in the season. Yeah, I think we'll probably be
1:11
in Vegas next year, which seems a little more normal for like a
1:15
conference, but. Vegas is not normal but for a
1:20
conference. Yeah.
1:21
So thanks for sponsoring this episode.
1:23
We're going to learn about Red Block today.
1:25
One of the things that we always like to find out is for our
1:27
first time guests, and this is the first time being with us, is
1:29
a little bit about sort of their identity journey.
1:31
How do they got into the world of identity or maybe security or
1:34
maybe both. So let's start there.
1:35
How did you get into the space of IAM or Digital Identity?
1:40
Well, I'm a programmer, I'm ACS grad and been dabbling with
1:45
writing code and most recently I did a startup in mobile security
1:51
that was like when iPhone 1 came out.
1:54
And very interestingly, iPhone one would not authenticate
1:57
against Active Directory. Active Directory, yes, and we
2:00
built a business enabling organization and employees to
2:04
access their internal resources. Cloud was not common back then.
2:08
So their SharePoint and their, you know, files on on network
2:12
shares. That's when I came to know, oh
2:15
this thing called Identity. And then that startup got
2:18
acquired the Oracle and amongst other things, I was APM for one
2:23
of the Oracle's Identity product for a period of six months.
2:26
So I got my exposure in Identity and you know, lo and behold, I'm
2:30
doing an Identity startup. So you're kind of an identity
2:33
lifer now you're at Red Block or you started Red Block, or I just
2:38
have to know. How did you come up with the
2:39
name? Well the name has multiple
2:43
layers so November ish of 2023 when I got this idea that hey AI
2:50
in its post LLM world is going to be multi model.
2:53
So ChatGPT 3.5 comes out and it makes it very easy to recognize
2:58
world objects. Not just a picture of a cat,
3:02
which the AI reasons as cat, or a dog, the AI reasons as dog,
3:06
but more context, such as if you show AI the picture of a lion
3:09
and say, Oh yeah, that's a cat family without actually
3:13
decoding, it's a picture of cat. And then we thought, hey, how
3:17
about we feed some screenshots of postures for web apps.
3:24
And lo and behold, it just detects beautifully that, oh, on
3:28
your Twitter screen, you have, you know, these access profiles
3:31
that you should not have. And then we started
3:33
experimenting and we thought, hey, why don't we build a
3:37
workflow that converts human actions into AI driven flows.
3:43
And then there was a big popular workflow too.
3:46
Let's not name them. And they had a blue box for all
3:50
the flows going into a ticket. So, you know, something happens.
3:54
And then of course, it goes to an ITSM where a human picks up.
3:58
And then he said, hey, why don't we change this to a red color
4:01
and the ticket goes to an AI driven human flow.
4:05
That's one of the layers of multiple red teaming as an
4:07
example, but that's one of. The yeah, that's neat.
4:10
So what is the underserved area or what is the market problem in
4:16
identity today that you feel is underserved, I think?
4:20
I'll give you 2 arcs on this, the arc 1.
4:23
And this is like a market answer, like a top level answers
4:27
for every dollar in cybersecurity, you know, this $5
4:32
spent on services, operational, staffing, human labour and just
4:38
getting things done like manually.
4:41
So if you look at the Tam of or the revenues of companies
4:45
collectively IN2024220 billion ish last year, cybersecurity
4:50
across the board, all products sold, sold, guess what the
4:55
numbers are for services and people enabling those products,
4:59
it's close to a trillion dollars.
5:01
Wow. And hate to say this, but there
5:05
is a laundry list of services companies and vendors and and
5:09
people that serve this market. If you tease identity smaller
5:14
section 3040 billion, close to $200 billion spent on services.
5:18
We thought, hey, how can we turn this into a category where
5:23
services are now enabled using AI driven software.
5:29
So that's the market we are going after.
5:30
It's a bigger arc on the top. But if you look tactically from
5:33
a buyer's perspective, they have a lot of work that gets stopped
5:38
by a ServiceNow ticket or a JIRA ticket.
5:40
So anything that you want to do in IT, automation or identity,
5:44
at the end of the day, it's a fulfillment job which you and I
5:47
will get, Hey, John, can you do this?
5:50
Hey, Jacob, can you fulfill this?
5:52
We are essentially routing that ticket to AI and let AI fulfill
5:57
that task. Instead of a ticket being
6:00
fulfilled by human, AI fulfills that ticket.
6:04
So with even with all the new spaces or you know, disciplines
6:10
within I am that are starting to kind of sprout up, I still think
6:14
the traditional approach is IGA access management or privilege
6:19
access management. I think though even with good
6:23
tools, it's lacking. What do you think?
6:27
It is lacking because if you look at the scaffold, ultimately
6:32
it's about do you have enough coverage?
6:34
Do you have enough visibility into your applications, your
6:37
identities? If you do not, it doesn't matter
6:40
whether IMIGA, Pam and now NHI and in future agents, your tasks
6:47
will not be done, your visibility will not be there.
6:50
So it doesn't matter whether you you move from one acronym to the
6:54
other. If you do not know how many apps
6:56
you have, what identities are inside those applications and
7:00
what entitlements are there, the gap is still there in the
7:03
market. So you're spending all of this
7:06
money to solve 10/15/20 percent of the problem where your back
7:12
door, your front door is closed, but your back door, your side
7:14
door, your garage door, your trap door for rodents still
7:18
freely accessible. And you know, that's where we
7:20
are going after. I think you just touched on a
7:22
little bit, but I want to talk about what is the urgency that
7:26
you know from a business perspective, what is the urgency
7:29
to go after this versus make investments in other areas of
7:32
identity? So if you look at the last 10
7:36
years of ransomware attacks or account takeover, so starting
7:42
from Target 10 years ago to Salesforce customer instance
7:47
breach of last year, there's so much in news.
7:50
Each of these companies had all the certifications, all the
7:54
compliance, all the tools, all the money, the best of the
7:57
people. This still got breached.
8:00
So it basically reflects on us as a community that isn't there
8:05
something that is not being served.
8:08
And the gap there is that the urgency that's brewing.
8:12
If you give it another thought, adversaries are no longer
8:17
breaching firewalls. They're no longer dropping
8:19
malware on your laptop. They're simply logging in.
8:23
So if credentials are the main primary vector, do you have
8:29
aggregated data of all the identities and the credentials
8:32
that are probably in the wild all the accounts that are in
8:35
your systems? So I think the urgency is what
8:38
are the apps that are not covered?
8:40
What are the apps that are not governed?
8:43
And I hate to say this but Infosec community has a
8:47
euphemism for this called last mile long tail.
8:50
As if they don't matter. Great.
8:53
But they do matter, because if you're sensitive data is in one
8:58
of those apps and that gets breached, it's a vector to take
9:01
over your infrastructure. So you talk about this gap,
9:05
right? You've got these disconnected
9:06
apps, you know, and you're totally right.
9:08
You say, hey, let's solve for 80% of the problem, and what do
9:11
you do with that last 20%? So you talk about governance.
9:14
There's a lot of governance tools out there already, right?
9:17
We've got Pam, we've got IGA. If I'm sitting here with my
9:21
famous jaded see so hat, it's like, OK, well, why do I need
9:24
another tool? Like why isn't Pam and IGA good
9:28
enough? Is it just the way they're
9:30
approaching it or is this like a new space?
9:32
Like what are your thoughts on that?
9:34
Yeah, it's it's a space that already existed.
9:37
So if I dovetailed my previous part that irrespective of all
9:43
the tools, all the all the technologies, all the
9:46
certification, all the compliance breaches have still
9:48
happened. And there's definitely a gap in
9:50
the market that we're not serving.
9:52
We're trying to solve the same problem.
9:53
We're trying to do visibility on the same things that are being
9:56
visible. We're trying to build a better
9:58
workflow for the things that we see, but we're not going after
10:01
the areas that are unseen to us. I'll give you an example.
10:05
So Okta we know as a, you know, IE governance and access vendor.
10:10
So they have this product called Okta Integration Network. 8100
10:14
ish apps are publicly listed there.
10:17
That means vendors that have come in and you know, put their
10:20
apps in there. If I tell you less than 5% of
10:24
those apps have any automation of onboarding, off boarding
10:30
changes and provisioning. The rest of the 95% are manual.
10:35
It's wild, Wild West. So John joins your org, he gets
10:39
access to everything that he wants.
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When he leaves, his access still lingers.
10:46
God forbid if those accounts are on Salesforce on Snowflake and a
10:52
credential theft and a spray and pre attack compromises that
10:57
nobody's paying attention. So it's a newer urgency that's
11:00
brewing. Go after the areas that have not
11:03
been seen. It's like my closet.
11:05
My wife doesn't want me to open because hey, you don't know,
11:08
babe, because we don't know what's inside.
11:10
You got a goddamn open it. So you mentioned another area
11:14
that is, you know, pretty common, right?
11:16
You talk about authentication and ID PS kind of getting in
11:18
that space of controlling access to resources, where does Red
11:23
Block fit into sort of like this triangle of opportunity slash
11:29
sadness that exists between authentication, IGA and Pam?
11:33
Is red block somewhere in those areas?
11:36
Is it something different? Is it a blend like Help me
11:39
understand, Kind of like the positioning?
11:41
So if you if you visualize this as a three legged stool, so leg
11:45
one is your IMIGA Pam monhumanidity everything else,
11:50
which is your visibility plane, which is your control plane,
11:53
which is a workflow engine, which is a policy engine.
11:56
And then the second leg is hundreds of micro legs which are
12:00
the applications. So you have your sales force,
12:02
your, your Zoom and your Slack and then 5500 internal
12:07
applications built by your team. So we come in between these two
12:11
legs and enable flow of data to give you visibility into those
12:18
1500 and of course a control plane so that you don't have to
12:21
file another ticket to take over access for a people who have
12:26
left or do governance on those apps or change entitlements.
12:29
So we kind of sit in the middle between the applications and the
12:34
governance and identity vendors. If I give you a better analogy,
12:38
think of Red Block as your DoorDash carrier.
12:43
We'll, we will take the order from you as a consumer, which is
12:47
your identity tool and then go pick up that order from the
12:52
restaurant, which is your apps and then without even looking
12:55
into it and deliver this. And then of course the
12:58
transaction happened. So kind of come in in the
13:00
middle. So you got me at the DoorDash
13:01
because I'm a big fan. But when you said DoorDash, I
13:04
started thinking, OK, well, this sounds a little bit like
13:06
orchestration is you're kind of you're picking up something from
13:09
one spot and then figuring out where it needs to happen with it
13:12
and then dropping it somewhere else.
13:13
Is that fair? Think of this as a last mile
13:17
execution. Your DoorDash app is the
13:21
orchestrator. It figures out oh go pick up
13:23
from restaurant 1, then go pick up from restaurant 2.
13:26
Combine those two orders. Deliver it to me.
13:28
So the orchestration engine is your door Dash app.
13:31
The guy who's fulfilling is the person, the carrier.
13:35
So we are the carrier. We're picking things up from
13:38
these individual applications. Hey, give me all the identities,
13:41
give me all the entitlements and the roles and API keys and
13:44
credentials and deliver it to me.
13:46
Boom, package it, give it to you and then say hey go do more
13:50
tasks and then go do that. So now I'm thinking logistics.
13:54
Logistics is a great word. So yeah, like, tell me where to
13:57
go, tell me what to do. We'll do this for you.
13:59
You don't worry about you still give me that trigger.
14:03
So we don't have intelligence of our own.
14:05
I hate to say this, my team doesn't like it, but we are
14:08
taking triggers from Sale Point, we're taking tickets from
14:11
ServiceNow and then doing the job which is supposed to be
14:13
done, OK. So let me keep my jaded CSO hat
14:16
on. And you know, this is probably a
14:19
question a lot of people know. So what makes Red Block special,
14:22
right? What do you think it is that
14:23
makes your product, your service, you know, different
14:28
from others that are in the marketplace?
14:30
So this problem existed for a long time.
14:32
So if you look at the the last mile execution, the automation,
14:37
you know, our PA vendors tried solving this.
14:40
You know, if you look at finance as a larger category, you need
14:43
to process invoices. So manually it's impossible to
14:46
aggregate. So you put an RPA bot there,
14:48
script it and you know, grab the data that colour has been kind
14:54
of an implemented in identity user degree for user access
14:58
review. So you need to aggregate
14:59
spreadsheets or user data. But RPA is scripted.
15:04
It breaks when you know the UI changes.
15:07
When the list of values simply changes, it breaks.
15:10
It almost like writing a piece of code that has supposed to be
15:13
executed. We are more, I haven't used the
15:16
word AI yet, so we are agentic. So think of us as the way we
15:21
work behind the scenes is we use computer vision.
15:24
So the AI looks at the screen visually, just like you and me
15:28
on the app and say, OK, what do you want me to do?
15:31
OK, here's the credential login. OK, what's next?
15:34
Grab the list of users, packages a Jason and give it to me.
15:38
So we're looking, the AI is looking at the screen and then
15:42
taking decisions and then extracting the information or
15:46
taking action and delivering it to you.
15:47
And that's the differentiates us, the more modern, if you want
15:50
to call it, there's no word around it.
15:52
It's kind of being coined agentic process automation.
15:56
And yeah, that's where it is. OK, so you've opened up the box
16:00
of AI and I've been thinking about, you know, when you kind
16:02
of first talked about those. OK, how do I formulate this
16:04
question? I'm going to put it rather
16:06
bluntly. Can I, how do I trust the AI to
16:10
do the right thing? Because now we're talking about
16:14
security. And so it needs to be auditable,
16:17
it needs to be traceable. You need to be able to explain
16:19
it, right? I think there's a lot of people
16:21
out there who are interested in sort of like, Oh yeah, sounds
16:24
cool, but how do I know it's making the right decisions?
16:28
Great question. So when we started this, the
16:32
demo version of the product that we have built now took us like a
16:35
week, but took us a year to put those guardrails around it.
16:40
Because when you're doing something with
16:42
identitysecurityyoucannothaveitgowrongitcannotdeleteawrongjohn@example.com, it has to be John, not Jon, if
16:53
that's the name, example.com. So we've built a lot of
16:57
algorithmic decision making. We built guardrails around it in
17:01
terms of how AI navigates. And I'm going to tell you this,
17:06
in our case, the AI does not make decisions.
17:10
The AI is doing analysis. And this is when you dig deeper
17:14
into the industry that we are going after, vendors or
17:18
competition. Oh yeah, you give the trigger
17:21
the task to the AI and the AI will figure itself out and
17:24
decide and take a decision. In our case, the algorithms, the
17:28
the guard rails, you know, the workflow that have inside, they
17:32
make decision. AI is the reasoning engine.
17:34
It's helping navigate. It's, it's helping figure out
17:38
what needs to be decided upon without AI deciding it.
17:41
There's a lot more work done. Technically, we have filed close
17:46
to a dozen patents on what we have built.
17:48
So it's not like indices skunk work in the garage and coming
17:53
out and party, but a lot of work that has been done.
17:56
I think the whole business case resonates with me where you
18:01
stand up a lot of these tools and it's like what you have to,
18:04
to get full value, you have to integrate hundreds of
18:07
applications in an enterprise scenario.
18:10
So that's where I think Red Buck fits and maybe you can confirm
18:15
that for me. But I'm also thinking from a
18:18
practitioner standpoint like how do I get this thing rolled out?
18:22
You talked about services in the beginning.
18:24
So for a typical customer, what does it look like to get started
18:28
and to actually start getting that value where it's like, OK,
18:32
now I've went from I've got 5-10 applications integrated to I'm
18:37
leveraging Red Block and I'm integrated to hundreds of
18:40
applications. And that's the challenge for
18:44
traditionally like you know, we have customers that just bought
18:47
a very popular IGA product and they are grappling with this
18:51
thought. They have 500 applications to be
18:53
on boarded and they quote got a quote from a services vendor.
18:57
It's a four year journey. So you essentially are waiting
19:01
for four years to discover every piece of identity in your
19:05
enterprise. You know, what's the analogy
19:08
there? You're a company of 10,000
19:11
employees and you do not know the 999 thousands of them
19:16
because it takes time to go interview and corral.
19:20
So we come in and we onboard these apps and app a day.
19:24
The process is very straightforward.
19:26
So let's say you have an app, let's call John's ERP engine
19:30
app, right? What are the IID operations?
19:33
Add user, remove user, change user and aggregate users.
19:38
So for each of these IE OPS, you just record a 25 second video of
19:42
how you and I as humans would interact with apps.
19:44
So you log in, you go click on that add user button in an admin
19:49
corner of the screen and that screen recording on any desktop.
19:54
It gets uploaded onto our studio and the AI crunches it for an
19:59
hour and it builds a turn by turn navigation of what needs to
20:04
be done. How it would be done when a
20:06
trigger from the governance tool or an access tool comes in in
20:10
real time and then it'll perform an action almost like an API
20:15
call going to the AI. It performs the action, confirms
20:19
it and closes a loop with the governance sender or with the
20:22
governance application, or with the Pam saying hey, rotate
20:25
credentials on hundreds of CCTV cameras in the supply chain.
20:30
It'll take a trigger from the Pam, do exactly I had described,
20:35
go log into each one of the CCTV cameras, admin console, rotate
20:38
the credentials, push it back to Cam, push it back to the Pam's
20:41
vault. Super cool.
20:44
I think if I was listening to this podcast right now, I'd
20:47
rewind about two minutes and have to listen to that again.
20:50
I think that seeing some kind of demo of what you just talked
20:54
about where you know, the you basically create recordings of
21:00
this administrative process, AI processes through that and then
21:05
learns how to do it. It's like, that's the dream,
21:08
right? It's like AI robots can take
21:12
YouTube videos and learn from them.
21:15
I think it's fantastic, Super cool.
21:17
So I want to see a demo. Hopefully you have that posted
21:20
on the red block dot AI slash IDAC.
21:24
We'll have the demo posted. And the kicker here is, which I
21:28
didn't mention so far, all of this infrastructure runs not in
21:34
our cloud, but in our customer's cloud.
21:36
So we serve banking customers, we serve regulated industries.
21:40
So we package the AI model, the platform as a virtual appliance
21:45
and hand it off as a binary. And it runs air gapped on their
21:50
own cloud or on Prem. So it doesn't push data to a
21:54
commercial model, Open AI or Gemini or anybody else.
21:58
It's our model that is talking natively on Prem or in their own
22:02
cloud does. That go for the training as well
22:05
so. Goes for the training as well.
22:07
OK. So let me make sure I understand
22:09
this. For me to set up a connection,
22:12
let's call it, you're watching my mouse movements, you're
22:16
recording the screen. I say, OK, this is the button I
22:18
press to do this thing. And then the system learns what
22:21
that looks like. And what happens if screens
22:26
change, UI changes? Do I I have to retrain like that
22:30
action again? Like how does you know what
22:33
happens if it doesn't click the right button or it makes a
22:35
mistake? Like, you know, I feel like I'm
22:37
the -1 for these are questions, I think, which is like, OK,
22:41
well, now I'm looking at a screen that might potentially
22:44
have sensitive information, a user Ida secret, you know,
22:48
something it's going into like this screen recording.
22:51
Like how do I safeguard to make sure that I'm comfortable as a
22:53
SISO or any other risk person to say, yeah, I trust this thing.
22:58
It goes back to the trust question I asked earlier about
22:59
AI. So.
23:00
I'll break this down in two parts.
23:02
Part 1. All of this training happens in
23:05
your environment. So the the video that you just
23:08
recorded for training the AI sits within your block.
23:12
Storage gets destroyed after the AI learns it.
23:15
It it's not needed, it's once. None of this travels to red
23:18
blocks, infrastructure or outside of your Prem.
23:22
Second, I'll give you an analogy.
23:25
So if you drive a Tesla or any FSD you're not training on a
23:30
daily basis. It has the model that
23:33
understands, OK, what's a pedestrian, You know, what's a
23:36
cone, you know, what's a, you know, moving object.
23:40
And it's navigating, deviating, maintaining the curvature of the
23:43
road as it would need be. And same thing for the web app.
23:48
Your colour of the button could change from blue to grey.
23:52
The placement could change from left to right.
23:54
It doesn't require retraining because when the AI ingests the
23:58
recording the training video for the first time, when it builds a
24:02
turn by turn directions, it's not hard coded coordinates nor
24:07
hard coded text of the button. It training itself based on the
24:10
intent of the screen. What's the intent of the screen
24:13
is to log in? Do I have the credentials,
24:16
username, password, second factor, multi factor?
24:19
What's the intent? Go to the next screen, go to an
24:22
admin section. So it's reasoning just like you
24:25
and I. Let's say you and I are on a
24:26
shopping site. We don't know where the checkout
24:28
button is. We can start with the URL.
24:31
OK, add, let's find the checkout button.
24:33
OK, not on this page, go to the next page.
24:36
AI is reasoning very similarly how you and I.
24:38
So we've trained it just like the human behaviour on a page.
24:42
See, Jeff, I think you asked that question, right?
24:44
Because you're interested. It's like, wow, this is really
24:47
cool. We need more, we need to dig
24:49
more. I'm thinking that.
24:54
So this works in coordination with your existing identity
25:00
infrastructure, IGA, your NHI solution, your Pam.
25:04
And I think you talked about that a little bit.
25:06
And I guess from what you said, the way I'm envisioning this is
25:11
like you say, all right, I'm going to give Jeff XYZ access.
25:16
You know, maybe in a manual environment you'd go out and
25:20
issue an ITSM ticket and a human being would go out and do that.
25:24
But instead red box and pick up that quote UN quote ticket.
25:29
And it's going to do that based on this training.
25:34
There's still got to be some kind of integration, right?
25:37
Some integration work with those IAM systems.
25:39
So talk to us a little bit about that.
25:41
So we are a sale point partner, we're Savion partner, we work
25:44
with Octa, work with Antra, Cyber Ark and others.
25:47
And we when we started, we did want to replace your the Csos
25:53
chess board. We are to come in and you know,
25:56
be a little bit more strategic around which pieces, what pieces
25:59
to move. So we integrate with, let's take
26:02
Sale Point as an example. We integrate the Sale Point as
26:05
if it's a native app connected inside the Sale Point universe,
26:10
so that if you're an admin, you're a user of Sale Point,
26:13
your business is on a daily basis as usual.
26:17
It would almost feel like that app, you know, John's ERP engine
26:22
is just magically connected using this API inside Sale
26:26
Point. So we work very closely.
26:27
So on the upstream side between Sale Point and Red Block is a
26:30
very tight coupling basic conform to their you know
26:34
connector framework and add an app as a new disconnected app
26:38
comes on board. So to your question, when you'll
26:42
say a request for fulfillment of let's say removing a user sale
26:46
point will happily send a trigger using an API call to us
26:50
saying hey, for this app perform this action, which is remove a
26:53
user for this attribute, which is the e-mail address, which is
26:57
a unique identifier where blocks engine is going to take it and
27:01
then perform the necessary AI automation behind the scenes to
27:05
remove the user. So it's just like a connected
27:08
universe on the upstream side, but by virtue of the AI being
27:11
brought in together. I guess sit here and ask, we
27:15
went through the why. I could just ask questions about
27:17
the how all day because I am interested.
27:21
I do need to understand again, so maybe we put this in a simple
27:26
explanation as possible. So how is it that you know,
27:29
traditional approach takes four years to get 500 apps
27:33
integrated, but Red block can do it in how long?
27:37
So traditional approaches, you know the numbers.
27:40
So let's say you have a brand new sale point instance, you're
27:43
a bank, you have 400 apps to go through, Sale point is going to
27:47
give. I'm just using sale point as a
27:48
proxy to large IE universe. So governance vendors will have
27:51
150 odd apps that have connectors out-of-the-box, which
27:55
means if you're lucky, the Venn diagram of what connectors are
27:58
available out-of-the-box versus your 500, you'll probably have a
28:01
match of 10/15/20. Boom, 10/15/20.
28:05
Done. You have 400 to go.
28:08
So then you put an RFP out, contact a services vendor to
28:11
write connectors for those 400 apps.
28:15
Averages $10,000 to $20,000 per app over a period of four to six
28:21
weeks. Lucky like a week now you're
28:24
looking at millions of dollars looking at a two to four year
28:28
timeline to bring those on board for us, we're not writing code
28:32
to connect these applications in there's no JDBC, there's no
28:35
Java. It's all driven by AI.
28:38
So you record a video, upload it, and the time that is being
28:42
set spent is for an analyst to confirm that the AI is behaving
28:47
exactly it's supposed to behave. And within a day or two, you're
28:51
giving a test data, hey, remove these 3 sample accounts and the
28:55
AI takes it, removes those 3 sample account, you're
28:58
satisfied. Boom, you take that unique
29:01
identifier off that particular app and then you add it in your
29:06
governance application. So you know, say points in Cyber
29:09
Ark or what have you, and then they're ready to take the
29:12
trigger. So, you know, when your
29:14
certification campaign is ready to run, the aggregation process
29:19
begins, a signal comes to red Block saying, hey, I need the
29:22
list of 10,000 users with the entitlements.
29:24
Boom, just an internal API call between Red Block and the
29:27
governance and the, you know, response gets sent similarly for
29:31
removal of a user. So the time is very shortened
29:34
compared to the years that I would take.
29:36
I'll give you a very specific example.
29:38
A customer that we're on boarding, they'll bring 150 apps
29:41
next year. They had a three-year quote for
29:46
close to 1 1/2 million dollars. So two-part question, let's talk
29:54
about that model. Is there something like you go
29:57
and help them kind of get kick started and then it's DIY And
30:02
then also like for a mature client who's actually, you know,
30:06
well into their program, how are they measuring the value,
30:11
measuring their success? So it's DIY.
30:14
The first part is that we kind of help with the 1st 15/20/10
30:20
and do a knowledge transfer and then shadow them for a period of
30:23
time. So we just gave a statement of
30:25
work to another bank and that's what we're doing like 25 apps,
30:27
we will do it for them and then shadow them for another 25 and
30:31
then they take over from them there.
30:33
The biggest ROI is at least the tangible ROI is time saved and
30:38
IT ticket is 40 minutes to 2 days.
30:42
You know the numbers of 90 days like mindless AI is going to
30:47
fulfill this in less than 3 minutes.
30:50
So you could shrink the time to 70 to 80% on a aggregate basis,
30:56
but in many cases on edge cases like by 99%.
31:00
So time saved equates to money. 2nd, if you are a very large
31:05
bank, you have let's say 90 apps under Sox or under compliance,
31:10
you have to perform the aggregation.
31:11
You're moving data around, you have CSVS and then if there's a
31:14
human error in one of the aggregated data, which is a CSV
31:18
file, you have three strikes before you get penalized.
31:22
So millions of dollars in penalties potentially are saved.
31:25
And I'm not even using reduction of threat vectors and attack
31:31
vectors because a rogue account, an orphan account was disabled
31:36
by AI. And let's be honest, the reason
31:40
the ransomware or the adversaries are active, not
31:43
because we don't have tools, but because we do not have time.
31:47
We do not have time to go look into each and every corner and
31:50
say, hey, have I covered all the identities?
31:52
Have I covered everything? Now the AI is scanning and going
31:55
and fixing this. So.
31:57
I'm going to ask maybe a stupid question, yes, because I'm
32:00
really curious about how this works.
32:02
How does it do the work? It's not an API, It's not an
32:07
API. So is it spinning up some sort
32:09
of like virtualized environment to like replicate a human doing
32:13
the work? It basically spawns A headless
32:17
browser. OK, so let's take the say the
32:20
governance example. You have request for a user
32:24
removal from access tool. Let's take save Point as a
32:27
governance tool. The API call from sale point
32:30
travels to red Block, normal API, nothing fancy.
32:34
The moment it comes, we spawn. Of course, there's a lot of work
32:37
done behind the scenes in terms of agent planning and all of
32:40
them kind of glossing over. But the the crux is a headless
32:46
browser gets spawned. And this headless browser gets
32:49
spawned based on the training that you'd we talked about
32:53
earlier, based on the URL, say John's ERP engine.com gets
32:58
launched, a set of credentials are fetched service accounts
33:02
from a Pam and that the AI is essentially performing the tasks
33:06
just like you and I would do, except there's no visual
33:10
monitor, there's no display adapter.
33:12
It's all being done in the memory somewhere in a data
33:14
center. There's nothing running locally
33:16
on your laptop. There's nothing running
33:18
adjoining the application where it is going.
33:20
It's all running remote in a headless environment, and then
33:25
of course the underlying models are helping decide what needs to
33:28
be done based on the trigger that comes in.
33:30
OK. And Jimmy hit it right in the
33:31
head and was like, I feel like I can ask how questions all day
33:34
long. My last, this probably isn't a
33:38
how question, but what are the limitations of this?
33:41
Because you mentioned a headless browser, I think.
33:42
OK, SAS yeah, makes sense. What about an on Prem
33:46
application like an SAP or some other thing that is, you know, I
33:50
would say not a modern application.
33:53
Something like that. As long as that legacy app.
33:58
So we have done some experiments.
33:59
We have not released the product yet.
34:01
If your mainframe can be proxied over a web browser, the AI can
34:07
still read and extract information.
34:10
It does not do well when you're a chain stuff.
34:12
Add attributes. So our current limitation is,
34:16
and this is a road map we haven't thought through yet
34:18
completely, can we solve for thick clients when you have a
34:22
desktop application running in your local laptop or a survey
34:25
environment? Right now our limitation is
34:28
anything that is web navigable. If you and I as humans can
34:32
navigate and solve the problem in a browser, bingo, Yeah, I
34:35
will do it. OK.
34:36
And I appreciate understanding that because I think a lot of
34:39
people say, yes, of course we can do it and then we'll figure
34:41
it out later. But I think of like, you know,
34:44
just kind of brainstorming. It's like, OK, well why not just
34:46
spin up like a little virtual machine, you know, of a Windows
34:49
or a Mac or a new Linux and run that thick client in the same
34:53
way where it would be kind of like a browser type thing.
34:55
So I'm not an engineer, I'm just thinking, you know, rudimentary,
34:58
but it feels like it's the art of a possible at that stage.
35:02
I think it's very early. So if you look at I'm going to
35:06
use the self driving as an analogy.
35:09
So 10 years ago Elon announced autopilot.
35:12
Of course, marketing jargon, but it did those three things very
35:16
well. Put it the car in the autopilot.
35:19
It will maintain the curvature of the laner Dr. it'll do
35:22
adaptive cruise control. Second, it do a very fantastic
35:27
lane change. You like tap it up and like veer
35:30
to the next one and then done third thing, it will park very
35:34
well, like parallel parking Bingo.
35:36
Like 10 years ago, unimaginable. But 10 years from now it is
35:40
almost like I don't drive anymore 99% of the time unless
35:44
you know, there's intervention because that's how it has it has
35:47
it has become. I think we are at the early
35:49
stage of AI driven automation. This is the first year.
35:52
This is the first year of the autopilot.
35:54
And for you the hype is so much you can actually call it almost
35:57
autopilot. I think we'll get there to the
35:59
Nirvana stage in the next 5-7 years.
36:01
So I appreciate the pun of AI driven and using the full self
36:05
driving analogies. I think it's a great analogy
36:08
because I remember the first time I had a Tesla a while back
36:11
and the first time you turn on the autopilot, you're like,
36:14
whoa, I don't trust it, right? Because you might drive a little
36:19
more on the left in the lane versus the right in the lane.
36:21
But you know, it generally sits right in the middle of the lane
36:24
and it follows the curves. But that first couple times when
36:27
you turn it on, you're very nervous.
36:28
At least I was like, all right, do I trust this thing?
36:30
But as I learned the system and understood, you know, the
36:34
limitations and where it excelled, I got very comfortable
36:37
with it. And yeah, it's a great feature.
36:39
So I love that. I, I, I, I really like the
36:41
analogy of the, of the FSD with the AI driven great, you know,
36:45
great connection there. Let me ask you a little bit
36:47
about 2025. Like, what do you think is like
36:49
the biggest thing that Red Block has, like, really come out there
36:53
and, you know, accomplished this year?
36:56
I think 25 started for us with a great bang in a way.
37:01
So we presented our first ever industry paper.
37:05
So we built our own visual benchmark.
37:09
So if you peel the onions of AI behind the scenes, it's all
37:13
driven by how performing it is. You ask the guard real question
37:17
how performing it is. And if I give and if you've
37:19
probably seen some of the open AI benchmark, like yeah, it can
37:21
now solve SAT it could, you know, clear the bar exam and
37:25
that those are the benchmarks. When we started this, there were
37:29
no benchmarks for visual reasoning because, you know, red
37:32
block is all about visual reasoning.
37:34
We look at the page and and the AI decides how good or bad it
37:36
is. So we presented our first ever
37:39
industry paper for visual reasoning.
37:41
I'm not going to go into details because it's going to take a
37:43
whole side track because based on 2 very popular game shows,
37:46
but let's keep it for later. And that was like early this
37:50
year in Abu Dhabi. I was there, we presented and
37:53
then we launched the the product.
37:55
So we went GA on April 29th, I think the first day of RSA, we
38:00
announced the product. We announced the product, not
38:02
just the product available. We actually took an NVIDIA GPU
38:06
cluster at our booth, the whole of AI running air gap locally
38:11
and doing the things I'm just describing like you know, JML
38:15
and AD user, aggregate user. And then we acquired the first
38:19
set of early customers for us. I'm really thankful short of
38:22
disclosing the names of some of the largest in the world working
38:25
with us because they're very progressive in their minds.
38:28
They have the problem that they have not been able to solve and
38:31
a small team that became slightly larger.
38:33
We now have like 14 people between Bay Area and Bangalore
38:36
so can't complain about anything right now.
38:39
So 2025 is like the coming out party, Yes?
38:42
What does 2026 look like? The winning party, the goal is
38:47
to, you know, get this in the hands of at least 20 brand new
38:51
customers. Many in conversations we have
38:54
not talked about the how publicly yet and I'm short of
39:00
almost stopping myself. Shall I say this?
39:02
Shall I say this not because what we want to talk most is
39:07
what is the problem they're solving.
39:08
If you go to website, the mention of AI is in the ratio of
39:12
the mention of security is at least 2-2 or five X.
39:16
The AI is not there that much. We talk about the problem that
39:19
we solve. I think next year the goal is to
39:21
talk a little bit more about how we do this and disclose some of
39:24
the papers that we have filed, some of the IP that we have
39:26
created. So that's the plan.
39:28
We're going to say acquire more customers.
39:29
That's why I was saying. So if there's one take away that
39:32
people should take away from this conversation, like what is
39:34
the plea to or call to action other than, you know, visit the
39:38
website redblock dot AI slash idac, right?
39:41
We'll have there'll be stuff there you can learn more.
39:42
But like what is something that's listening to this
39:45
conversation? Like, all right, so I've just
39:46
heard about this thing called. Redblock Now what if you have
39:51
applications that are not connected, applications that do
39:54
not have APIs and you know Gartner is calling that category
39:58
as disconnected apps? You know, talk to us, give us
40:01
like a day and give us an app. We will get this up and running
40:05
in our sandbox or yours and then perform these actions what you
40:09
always want to do. But unfortunately you sent it to
40:12
an IT ticket AI will fulfill it in minutes.
40:14
Instead of, you know, you're relying on somebody who's
40:16
watching Netflix or on vacation, then it's going to come back and
40:19
close the ticket. AI will close it in like 3
40:20
minutes. So you just, we're here at the
40:23
Gartner Island Summit in Grapevine, TX Amazing, yes,
40:28
everybody's dream to come here someday.
40:31
No, you presented yesterday. You've been at this conference
40:36
now for a day and and change. What's your impression of the
40:40
conference and tell us a little bit about your presentation.
40:43
Yesterday. So I think we still at the
40:50
what's the right word? I think we're still skeptic
40:53
about the use of AI in identity. We still kind of walking tiptoe
40:57
into this territory that, hey, can AI solve this problem or
41:01
not? Luckily, there's lesser of a
41:05
negative chatter on AI doing damage, which was kind of
41:09
relieving for me when I was at the keynote yesterday.
41:12
It was a little bit more balanced versus the other any
41:17
events I've been to. It was like or the the online
41:20
chatter is how AI is going to do more damage.
41:23
The Terminator, I think the the my take away is we're still a
41:27
little bit more skeptic, but just like any other new
41:30
technology, be a typewriter, be it the Gutenberg press or be it
41:35
the Tesla, self driving as humanity, you got to experiment.
41:38
You got to figure out whether this is going to work for us.
41:40
Of course there'll be bad actors, but we cannot stop
41:43
innovating. But because of they're bad
41:45
actors in the world, I think my impression is you'll be a little
41:48
bit more aggressive about this. You'll be a little bit more
41:51
forthcoming about experimenting, adopting of tools.
41:54
I mean, that's my take away from like day and half.
41:57
Yesterday I talked about, you know, it was mostly how there's
42:01
a gap in the market and how the attack surface is super exposed
42:07
because there's more and more apps, you know, the explosion of
42:11
apps. You know, you and I are old
42:13
enough. I remember I had like 5
42:15
applications on my desktop. That was my word.
42:18
Now the team that I have, they have 50 applications, you know,
42:21
SAS and internal. So that app explosion is the the
42:26
driving force and then agents coming in.
42:30
So you no longer are your one person doing the thing, you have
42:33
10 delegates doing the thing. So how are you going to manage
42:35
all of this? Yeah.
42:37
So what themes are you seeing or conversations you're having here
42:41
at the conference that make you optimistic for the future?
42:45
I think there is some conversation around non human
42:49
identity and how guardrails have to be input around agents that
42:54
will access credentials. So I think people are thinking
42:57
about it, people also thinking about permissions.
43:00
So if I allow an agent to do a task, is it static?
43:05
Is it dynamic? How can I do just in time?
43:08
So I think they're thinking around on the edges of what
43:12
should be the art of possible allowing AI to do the task, but
43:16
with the guardrails and with the permissions around it.
43:18
So I'm very hopeful that as innovators, as an industry in
43:22
general, will solve this problem and we'll get to it.
43:25
However, my only worry is that we have not fully solved the
43:29
human identity problem. I hope we accelerate that.
43:33
What's not being emphasized enough?
43:35
What are you concerned that we're not paying enough
43:38
attention to? I think the privileges the are
43:41
the the issue of over permissioning is still rampant.
43:46
If I join a company, I need access to 25 systems.
43:49
I clamor. I Hume and cry and fight.
43:52
I get 25 of those GitHub repositories.
43:54
Just take that example. When I leave or when I change
43:57
roles, I still have access to sensitive repositories and data.
44:01
I think it's not enough attention being paid towards
44:04
over permissioning privileges accumulating static privileges.
44:09
I think that requires rethought all right.
44:11
Final question. This is not a financial
44:14
question. This is a question about, you
44:20
know, from the perspective of the technology.
44:24
Are we in an AI bubble? We are, I think, I think this is
44:31
our human mind. I, I don't want to be negative
44:34
about it. It's a human mind, right?
44:36
There'll always be a group of people, all of us combined.
44:39
They'll be excited about something that is new because as
44:42
a kid we want to play with the toy, but then there are hundreds
44:46
of kids wanting to play with the toy.
44:48
So the toy manufacturers are out of control and hence there's a
44:52
lot of money being pumped in on technology that's not proven.
44:56
So which is good and bad. Good that it brings out the
45:00
best. Bad that the best ones do not
45:04
have access or capital to let the technology see the light of
45:07
the day. So if you are connected with me,
45:11
I am running a fund of a billion.
45:15
I will let you try that for a $10 million check.
45:18
But am I doing disservice? Probably, yes.
45:23
I should look out for other. I'm not saying anything against
45:27
our relationship, but there could be better use of this
45:31
money to invest in startups or technology to, you know, do a
45:35
better good study. So it has to be more controlled.
45:37
It has to be steadfast rather than, hey, let's just go invest
45:40
all the money possible. You've seen that story in in the
45:44
web era, 96 to 99. Everything that was promised
45:48
went out of business, but everything that was promised
45:52
ultimately was delivered over the next 10 years after the
45:55
bubble. So all the web, all the SAS, if
45:58
we go back in time, Oh yeah, shared drives.
46:01
I remember startups that were raised hundreds of millions in
46:04
shared drives went out of business.
46:05
But what's proper now? Google Drive, Box and Dropbox
46:08
born after the bubble. Well, blast of my past.
46:11
I'm thinking of my zip drives that I used to have.
46:14
Oh, yeah, I can store 250 megabytes on it.
46:17
Oh my gosh, there's so much room now, right?
46:20
It's been a really interesting conversation.
46:21
I definitely want to like learn more about this.
46:24
So again, go to the website, you know, red block dot IAI slash
46:27
IDAC. We're kind of getting to know
46:30
each other before we hit record here.
46:32
And we were talking about flying, like, literally flying
46:35
planes. So I want to know how you got
46:38
into, you know, being a pilot and what do you fly and when are
46:43
we going to go flying? So every kid has the same dream,
46:48
all of us, right? I want to be a guy riding the
46:52
fire engine. I want to be a pilot riding a
46:55
plane. Guilty.
46:56
I wanted to be a pilot. Yeah, all of us have the same
46:59
dream. But you know, we get busy, life
47:01
catches on, we get family, work catches on.
47:04
And when I moved to the Bay Area, I grew up in India, of
47:07
course, air travel. Now it's a Papa and I grew up
47:10
with no air travel. And then when I moved to the Bay
47:13
Area, I did not know I started living next to an airport.
47:17
So I live in East Bay in a small city called Dublin, which is
47:20
like 1 1/2 miles from the Livermore Airport, which is a
47:23
local Municipal Airport. It has two runways.
47:25
Fantastic. Both of them are good use.
47:27
And one fine day without telling my wife, I went on a Discovery
47:31
flight and I was free. And then the flight ends very
47:36
well and I registered for a flying class and for an offline
47:41
training class where they teach you the theory.
47:43
So essentially, without telling my wife and my family, I started
47:46
training for a pilot where I have to clear a written exam and
47:49
an online and in air exam or behind the wheels tested zip
47:54
code driving the car and low and both few years later, I I am now
47:58
flying a single engine Cessna. So I'm like, yeah, normal single
48:01
engine Cessna pilot, which can take one or two passengers and
48:05
then not go out beyond 304 hundred miles of my local
48:09
airport. So it's fun and you're most
48:11
welcome to join me whenever. Can they stay in the Bay Area?
48:15
How long did it take you to get your pilot?
48:17
License. I did, I think 6668 hours over a
48:22
period of a year, OK. So I've been flying like flight
48:25
simulators since I was in my teens, right?
48:28
So I feel like, you know, there's, there's this, you know,
48:31
feeling that if you've played video games, a lot of people
48:34
there was like a study is like, well, you know, if the plane
48:36
ever says we need a pilot, right?
48:38
Anybody who's played video games, like a flight game is
48:40
like, yeah, I can fly a plane. I I think it's, I think it's so
48:44
cool to have the time to be able to do that and the investment to
48:48
be able to like do that. Like what's next from like a
48:51
flight perspective? Do you go to a larger plane or
48:55
are you like, I'm good with the Cessna and like tell me about
48:59
like where the next part of the journey is?
49:01
Do you have more than an hour on this?
49:04
We could do it all the time. I was on it, yeah.
49:06
So what we've so the pilot journey is very similar to an
49:10
identity professional journey. I'm just kidding.
49:13
So the pilot journey is you basically, hey, I want to do a
49:15
discovery flight. Then you become what is called a
49:17
VFR pilot. So visual flying rules
49:20
essentially you visually look at stuff.
49:23
Of course, you have a map, you have a guide, you look at
49:25
objects. You cannot fly within or inside
49:28
clouds. It has to be 100% clear a day
49:31
before you can fly. So the next step is you get IFR,
49:34
which is instrument flying rules.
49:36
You can blind, not blindfold, but you don't probably look over
49:39
the cockpit or the horizon. You can just look at the
49:42
instruments and you can still fly because now you're using
49:45
guided instruments and automation and helping and then
49:47
fly. The other part is you go from
49:50
single engine to double engine, you go to jets, you go turbo
49:54
profs, you go, you know, Boeing's and the larger jets,
49:58
which is thousands of hours of flying, don't have patience,
50:01
don't have time. That not becoming a professional
50:03
pilot yet, at least not my bucket list.
50:07
I think VFR to IFR is a very simple journey.
50:11
It requires another probably 50 to 100 hours of investment.
50:15
If you take another exam, you have to have another examiner in
50:19
the plane clearing you. And of course then you could fly
50:22
anywhere. You could go above 10,000
50:24
because then visual flying as a rule and all that.
50:26
So just follow I. Think it would be so cool, Jim,
50:29
like, you know, we do consulting during the day like why don't we
50:32
just fly to the client, right, rather than drive or take a
50:35
commercial. It's like, hey, let's get a
50:37
little plane and, you know, take off and.
50:39
Nobody to bother you up in the air.
50:41
You just by yourself, if not your wife or your friends or
50:44
your family, just aim for the sky, just going somewhere.
50:47
I think the visual and the instrument guided a big leap,
50:52
right? It's a big leap.
50:53
From my understanding, most of the accidents are with the
50:58
instruments, people not trusting them and and kind of like saying
51:02
Oh no, they feel like they're flying in a circle or something
51:05
so they go the other way, don't trust the instruments, and then
51:08
end up in an accident. Well, if you know the stats,
51:13
most of the accidents are people trusting themselves too much.
51:18
Most of the accidents are not on a bad weather day, but on a
51:23
clear weather day. This is like a very jarring
51:26
statistics from FAA. 56% of accidents are not in the air but
51:35
near the airport, whether you're landing or taking off and some
51:38
obstruction. And the majority of them I don't
51:41
have the numbers are on a very fine day because they Oh yeah, I
51:44
can see through it and then relax, soak it in and next year
51:48
something goes wrong. I always find it fascinating.
51:50
You know, I fly a lot of out of the Atlanta airport a lot, you
51:53
know, very busy. And when you hear about like
51:55
planes colliding, you know, in the terminal and on the gates,
51:59
you know, and, and stuff is like, these are giant planes.
52:02
Like how do you mess that up so badly?
52:06
There's a distraction. I think as individuals we are
52:09
more distracted, we're not paying attention.
52:11
We have become like a goldfish brained and accidents have
52:15
happened more recently than earlier.
52:18
So can we get to full self flying at some point?
52:21
I know a lot of, you know, commercial flights are automated
52:24
to some degree, even with like iOS systems for instrument
52:27
landings and stuff like that. Not every airport has that.
52:30
But, you know, we're coming to the point where, you know, an AI
52:35
can essentially fly the plane for you as long as the
52:37
instrumentation is correct, right?
52:39
And the hardware is there. Like how far away do you think
52:41
we are from like pilotless planes?
52:45
I think pilotless planes are far away because especially on
52:48
commercial side, if you look at let's take A380, a 350, Boeing
52:52
77 Sevens and the modern planes and Dreamliners, 90% of the
52:56
flying is automated today because of the autopilot.
52:59
It has a plan fed in and it just guides itself on the way unless
53:03
there's intervention. The landing and take offs are
53:05
still very manual, very pilot intervened.
53:08
Technology is there to automate it, but I think the rules and
53:12
segregation in the last minute, you know the ATC intervening
53:16
because there's a plane which is delayed in take off etcetera.
53:20
I didn't take time. I, I think it's OK in my mind,
53:24
you still want, at least if I am one of the 150 passengers in my
53:29
Southwest, I want the pilot to be there.
53:32
You know, just like your Waymo or your Tesla.
53:35
So Tesla still requires you to be sitting as a driver in Waymo.
53:39
I'm sure you've taken Waymo's. The sheer fact that there's a
53:43
steering wheel gives a sense of calm.
53:47
And there was a discussion last week with someone, I forgot the
53:49
name of the person, he said. Oh man, if they could put a
53:52
dummy there it would given me even more sense of calmness
53:56
because it make my mind feel that somebody's there, although
53:59
the dummy's doing nothing. Now I'm thinking of the movie
54:02
Airplane with the dummy copilot inflatable that comes up.
54:06
And this has been such a fascinating conversation.
54:08
I feel like there's so much more.
54:09
Again, so many hows like how this works, you know, we'll
54:13
point people to the website. It'll be in our show notes and
54:15
things like that for people to check out, connect with you on
54:17
LinkedIn, you know, that kind of stuff.
54:19
So really appreciate you taking the time with us, sponsoring an
54:21
episode, getting the word out. You know, this is the coming out
54:24
party. Let's you know, cheers to a
54:26
great 2026. And yeah, so we'll leave it
54:29
there for this week. Thanks everybody for watching
54:31
and listening. You can find us on the web, IDC
54:33
podcast.com, like and subscribe, do all that fun stuff.
54:36
And yeah, we'll leave it there. Thanks for take care.
54:41
You've been listening to Identity at the Center.
54:45
We hope you've enjoyed the show. Make sure to like, rate and
54:49
review, and we'll be back soon. But in the meantime, hit the
54:53
website at identity@thecenter.com.
54:57
See you next time on Identity at the Center.