01 / 15
The agent OS for enterprises
Enterprises can't buy
agentification because
they can't imagine it.
We give them the lens — then we build, run and govern the whole fleet.
RAISING ₹2 Cr · CCD
TERMS ₹75 / 125 Cr · 15% discount
STATUS One-third committed
olbrain.com
August 2026
Problem
02 / 15
The problem
Enterprises are full of work agents
should be doing, and no way to see it.
We have shown the platform to six enterprises — from two-person businesses to a listed
manufacturer. Every one of them came back with a list of agents they wanted built.
Nobody can write a specification for something they have never seen. So the demand exists
and never becomes a purchase order.
95% of Indian organisations have begun
14% are past early validation
2% have deployed at scale
14% are past early validation
2% have deployed at scale
olbrain.com
Problem
03 / 15
Why now
The pieces landed in the last eighteen months.
Nobody has assembled them.
Models became reliable enough to act
Multi-step tool use crossed from demo to production. An agent can now be trusted to complete work, not just draft it.
Integration stopped being bespoke
A standard protocol for connecting agents to enterprise systems removed the largest cost line in every deployment.
Context became affordable to hold
Compression made a persistent identity economically viable. Two years ago the inference bill made it impossible.
And the first wave disappointed
88% of agent pilots never reached production. Enterprises now know what they do not want — and are ready for something structural.
Eighteen months ago this could not have been built. Eighteen months from now the category will have a name
and a leader.
olbrain.com
Solution
04 / 15
The solution
We show them. Then we build what they saw.
First, the lens
One session. An engineer who built the platform runs it against the prospect's own business — their files,
their workflows, their numbers. Not a deck, not a case study.
Within an hour they stop watching and start listing. Every enterprise we have shown has produced its own roadmap, unprompted, in the room.
Within an hour they stop watching and start listing. Every enterprise we have shown has produced its own roadmap, unprompted, in the room.
Then, the build
Agents build the agents. A fleet of specialist agents reads the enterprise's own files, recovers how the
work is actually done, and writes the agents that do it. Nothing is authored by hand.
The sixteenth agent costs what the third did. A new agent is configuration, not a build.
The sixteenth agent costs what the third did. A new agent is configuration, not a build.
Enter
Wherever it hurts most. The entry point is theirs to choose, and it does not matter which.
Expand
They name the next agent. We have never had to propose one.
Compound
Everything the fleet learns accrues to one place, and stays.
olbrain.com
Product
05 / 15
The Enterprise Brain
Everyone has wanted this for years.
Nobody will authorise it.
A system that knows everything a company knows and can answer anything about it. The value has never been in doubt. But no enterprise grants one system total access to everything it has — that proposal dies in security review before it is costed.
So we never ask for it
Each agent needs one narrow slice of data to do one specific job. Every grant is small, justified, explicit
and easy to approve.
Nothing is taken that was not given. It simply accrues.
The brain assembles itself out of permissions nobody had to think twice about.
Nothing is taken that was not given. It simply accrues.
The brain assembles itself out of permissions nobody had to think twice about.
One agent
A narrow view. One function, well.
Twenty agents
A picture of the business. Support knows what inventory knows; finance sees what procurement changed.
Two hundred agents
Anyone can ask it anything — or ask it to produce the analysis, the deck, the document — within whatever each role is permitted to see.
olbrain.com
Product
06 / 15
How it grows
One agent becomes a function.
A function becomes the organisation.
When a department head sees what another function now has, she wants it for hers. The pattern runs down the org chart on its own — every level of an enterprise has someone estimating what the level below already knows.
Entered through
One research agent
→ 8
requested, unprompted
Entered through
Five workflow agents
→ 15
scoped by the client
Entered through
A financial projection
→ 11
built and in scoping
Entered through
Customer support
→ brief
then the whole business
The end state is an enterprise that can answer for itself — where anyone in it asks the business a question
and gets the answer, not a request to someone else.
olbrain.com
Solution
07 / 15
Go-to-market
We don't sell. We show.
There is no vendor list for this and no analyst quadrant. When an enterprise decides it needs agentic AI, it asks people it trusts — and our name comes back.
How the last five reached us
A founder heard a lecture
on agentic AI for enterprises and made contact the same week.
A founder told a friend he
needed a platform. The friend told our advisor, who introduced us.
A chief executive asked a
former client of ours to find someone. He pointed to us.
A champion who had worked
with us moved companies — and brought us with him.
We knew none of them. Every one of them found us.
Then the demo does the work
Run against the prospect's own business by the
engineer who built the platform. They leave with a list they wrote themselves. Cost of acquisition: one
engineer's afternoon.
And it scales with engineering
One hire adds build, deployment and demand
generation at once. There is no second organisation to fund, and no salesperson to train.
The honest constraint
Today it is a founder's name that comes back.
It has to become the company's — which is what every deployment we can speak about buys.
olbrain.com
Traction
08 / 15
Traction
One deep engagement. Four more,
deliberately.
The concentrated bet
A fleet of five agents producing the quarterly
financial projection for the finance function of a listed manufacturer — reproducing the
client's own figures to the paise, with the next six already scoped by them.
Commercial approval stage
Client drew the next two phases
Finance, then every department
Client drew the next two phases
Finance, then every department
And four others, across four industries
Two-person online retailer
Support agent live in production. First revenue 5 September.
Research-led consultancy
One agent tested; eight more requested. Deploying.
International recruiter
Screening agent scoped the day after the demo.
Mid-size lender
Fifteen agents identified. Paused on their side; sponsor returning.
Why not all of it on one account. Full agentification depends on a champion
who stays and a sponsor who stays engaged — neither is in our control. We have already had a fifteen-agent
programme stop because a CFO retired and the sponsor was consumed by an acquisition. Four more accounts is
redundancy, not scatter.
Pre-revenue until September. ₹12L monthly burn, seven people, founders
unsalaried. The company cannot be ended by running out of money.
olbrain.com
Market
09 / 15
Market
India is where the position is earned.
It is not where the market is.
SOM · by Jan 2030
₹100 Cr
Exit ARR. Roughly 120 enterprises running about 2,000 agents.
SAM · India
₹4,600 Cr
~3,000 enterprises above ₹500 Cr revenue, at mature pricing.
TAM · global
$8–15 bn
India is under 3% of worldwide IT spend. The same layer, everywhere.
We are not taking share of an existing market. Almost no enterprise has committed to an organisation-wide
agent layer — the category barely exists.
Every demo converts an enterprise from having not considered it to counting agents.
The market grows because we show it.
The monopoly test is not installed base. It is share of new deals — when an
enterprise decides to become intelligent, is there a second name on the list?
olbrain.com
Market
10 / 15
Competition
Two questions place every vendor. One quadrant is our game.
▲ The entire agent fleet
Q2 — Developer & low-code platforms
Frameworks
LangChain / LangGraph · CrewAI · NVIDIA NeMo
Cloud building blocks
AWS Bedrock · Google Gemini Enterprise
Low-code & orchestration
Microsoft Copilot Studio† · Dust.tt · Vue.ai
Tools. Your team assembles and operates everything.
Q4 — Agent-native fleet platforms
Hand-built
Agent-built
Persistent
identity
identity
Palantir AIP — the ontology is declared, not recovered. Resident engineers, quarters not weeks.
Olbrain
Session-
based
based
Phronetic · kAIgentic · Nexus
FDE armies — Microsoft Frontier, OpenAI embedded engineers
FDE armies — Microsoft Frontier, OpenAI embedded engineers
Kore.ai · Adya.ai
authoring automated; humans still run and govern
authoring automated; humans still run and govern
Speed is why an enterprise buys.
Persistent identity is why supervision falls — an agent that resets cannot learn from a mistake, only recall one.
Q1 — Function-specific toolkits
Voice-agent toolkits
Vapi · Retell AI
Conversational builders
SigmaMind AI
Task-level APIs
Arya.ai (Apex)
Q3 — Finished agents & copilots
Retrofit platforms
Salesforce Agentforce · ServiceNow
Suite copilots
Microsoft 365 Copilot · SAP Joule
Vertical agent products
Sierra · Decagon · NovaHQ · Allyra
Conversational-AI products
Yellow.ai · Haptik · Gupshup
◀ Your team builds it
One function, channel or suite ▼
You receive working agents ▶
Every one of them sells a way to build agents.
None of them tells an enterprise what to build. That is why the field is loud and 2% have deployed at scale.
† A retention layer — it lets the Dynamics installed base feel agentic without migrating.
Placements reflect public positioning, not audited architecture.
Placements reflect public positioning, not audited architecture.
olbrain.com
Defensibility
11 / 15
The moat
A loan officer earns a ₹5 crore limit over
fourteen years — then retires with it.
Every enterprise already runs on delegated authority. A person starts with a small limit, builds a file — decisions, outcomes, judgement — and the limit rises as the record justifies it. It is how institutions scale decision-making, and it has one flaw: the judgement leaves when the person does.
An agent that resets cannot participate
Every decision is made by nobody in particular, so no file accumulates. The limit never rises — and someone
checks every decision forever.
That review is the entire cost. An agent that removes 40% of a task but needs 100% supervision has removed almost nothing.
That review is the entire cost. An agent that removes 40% of a task but needs 100% supervision has removed almost nothing.
Ours has a file
One accountable actor across time, with values, beliefs and drives that persist and update. Every decision
attributable, every outcome scored against it. When it is wrong, its judgement is different afterwards — not
merely better informed.
And it does not retire.
And it does not retire.
Coherent
A mistake only exists against consistent values. Contradictory drives mean nothing registers as failure.
Continuous
It holds I judged this way, this happened, I judge differently now. Otherwise learning is indistinguishable from drift.
Not copyable
A record that transfers by duplication belongs to nothing. Authority cannot be delegated to a template.
olbrain.com
Business
12 / 15
Business model
Charge for building the agent,
and for the thinking it does.
How we charge
| ₹20,000 per agent per month | Subscription |
| ₹2 per message · ₹1 per workflow step | Usage |
| ₹5,000 per research report | Usage |
| Inference, compression, storage | Bundled |
Why bundled, not passed through
Every rupee taken out of inference cost is margin we
keep, not a discount we hand back. Moving workloads to open models becomes a business lever.
01
Olbrain gives a way to think
02
The demo is the product
03
Enter from wherever it hurts most
04
The Enterprise Brain accumulates for free
Usage overtakes subscription as fleets mature — and it grows without a sales conversation, because we add agents
to a client's fleet ourselves.
olbrain.com
Business
13 / 15
Projections
₹5 Cr. ₹25 Cr. ₹100 Cr.
Exit ARR at the end of each year. Driven by accounts deepening, not by client count — agents per enterprise roughly doubles over the period.
| At 31 December | 2027 | 2028 | 2029 |
|---|---|---|---|
| Exit ARR | ₹5 Cr | ₹25 Cr | ₹100 Cr |
| Enterprises | 20 | 50 | 120 |
| Agents live | 150 | 600 | 2,000 |
| Agents per enterprise | 7 | 12 | 17 |
| Headcount | 35 | 80 | 150 |
The sensitivity is depth, not breadth. At 12 agents per enterprise in 2029
the figure is ₹70 Cr; at 25 it is ₹145 Cr. Winning more logos moves it far less than going deeper in the ones we have.
No revenue is modelled from white-label or channel partners. Both are live
conversations. Both are upside to this case.
olbrain.com
Team
14 / 15
Team
Two founders. Five engineers.
Output is not linear in headcount.
Alok Gotam
FOUNDER & CEO
IIM Ahmedabad. Built AutoML at Hotify.AI — acquired. Built AI-Aviator for military UAVs at Dilaton. Twenty-five years on machine agency.
Nishant Singh
CO-FOUNDER & CTO
IIT Kanpur. Architect of the core algorithm behind Aadhaar — identity at 1.3 billion scale. Ranked 5th globally, Animal-AI Olympics 2019.
How we hire
Batches of interns every three months; roughly half graduate onto the team. They build, they demo, they deploy.
The platform makes juniors productive — so we do not compete for scarce senior AI talent.
Advisor
Pankaj Thakar — founder, PadUp Ventures. Eighteen months of weekly engagement.
olbrain.com
15 / 15
The ask
₹2 Cr to answer one question.
Does a demo convert to a paying deployment at 10% or better — run by an engineer who is not a founder?
Instrument
CCD · ₹75 Cr floor / ₹125 Cr cap · 15% discount
Committed
One-third, by existing investors
Runway
Twelve months · 15 people · founders unsalaried
The gate — August 2027
150+ demos15+ paying accountsConversion above 10%A named enterprise reference
If conversion comes in under 10%, the thesis is wrong — and this round is what it cost to find out.
alok@olbrain.com
olbrain.com