The Agent OS
your enterprise can trust.
Run, Govern, and Build agent systems across the enterprise, starting with FP&A.
Finance needs a current view
of where the business is heading
At the first enterprise co-build, finance updates its quarterly forecast each month. The team compares actuals, budget and projections before presenting the result to management.
Find the inputs
Financial models and operating inputs from different owners.
Establish the number
Check the forecast against its sources and assumptions.
Explain what changed
Explain what changed and test management's questions.
FP&A is the entry point into the work that supplies every forecast.
Many agent systems.
One operating system.
An agent system combines one or more agents with the data, tools, workflows, and governance required to achieve one defined business objective.
Enterprises Run, Govern, and Build agent systems on Olbrain.
FP&A review
AGENT SYSTEM
Sales planning
AGENT SYSTEM
Procurement
AGENT SYSTEM
Illustrative agent systems for distinct business objectives.
₹2.6 Cr raised to build
the Agent OS
The FP&A co-build uses the existing Agent OS and extends it for enterprise deployment.
This round funds deployment depth: agentify one enterprise on the platform already built.
GitHub audit, 23 September 2026: 72 repositories including 5 archived; 21,418 default-branch commits; 1,841,336 source lines. Team size supplied by founder. Enterprise outcomes remain to be proven.
One FP&A agent system.
Five agents working toward one objective.
The first phase reproduces the finance team's forecast using its own methods. A later phase will test an independent projection against actual results.
Reader
Reads source files and drafts structured inputs.
Asker
Requests missing inputs from their owners.
Analyst
Reviews assumptions against evidence.
Detective
Explains movements between forecast versions.
Writer
Drafts the narrative for review.
Deterministic arithmetic from human-confirmed inputs.
Designed for finance to check sources and for management to explore scenarios.
An active FP&A co-build
with a large Indian enterprise
Customer methodology
Selected forecast figures checked against the finance team's manual calculations.
Direct finance involvement
Feedback on projections, precision and stakeholder requirements is shaping the system.
Build and validation
Closing open points before review with the next stakeholder.
Next commercial proof
Approval, paid production and recurring use.
Co-build evidence; no paid production or measured savings claimed. Upstream data integration has been discussed.
Finance needs a result it can use.
The enterprise must trust how it was produced.
Know who acted
Self-identity and action records connect an agent’s role to its activity.
Control what happens
Permissions and approval steps keep decisions with the people responsible.
Inspect the result
Source references, confirmed inputs and reproducible calculations support review.
The finance outcome motivates the purchase. Trust makes deployment acceptable.
Self-identity and signed action records are in the current platform. Stronger cryptographic identity enforcement remains in development.
Enter through FP&A.
Agentify the enterprise.
The first system opens two paths: deepen finance and expand across functions.
FP&A ↑
FP&A forecast system
Continuous FP&A
Connect more source processes; test projections, scenarios and alerts.
Hiring · service · operations
Agentified enterprise
Many business objectives, each served by an agent system on Olbrain.
Prove enterprise deployment.
Then repeat the entry
Large enterprises with recurring FP&A decisions.
Olbrain working estimate; account-by-account qualification remains to be completed.
Recurring forecasts, inputs spread across functions, a finance lead willing to work with us, accessible data and a path to purchasing.
First prove cross-functional deployment and customer handover in one enterprise. Then apply that experience to the next.
Enter through FP&A
Prove the first system against the customer's own work.
Expand within the account
Build systems in finance and other functions.
Hand over the platform
Enable customer engineers to keep building and running systems.
Repeat elsewhere
Use the deployment experience to enter another enterprise.
Subscription and usage.
Revenue expands with published systems.
An Agent System serves one business objective. Its subscription reflects the Agents it publishes and any shared-interface orchestrator.
₹10,000 / organisation / month
Platform fee from organisation approval.
₹19,800 / published Agent / month
Prepaid after the Agent System’s 30-day free period.
Orchestrator, usage + delivery
Orchestrator: ₹2,500 / month · Response: ₹2
KB indexing + storage: ₹337 / GB-month
Olbrain FDE: ₹9,500 / FDE-day, when approved.
Exit subscription ARR
74 paying enterprises · 4,165 paying, published agents. Storage, usage and other non-Agent charges are excluded from ARR.
Agent, orchestrator and conversational-usage billing starts after one 30-day published free period; the organisation fee starts on approval. Responses are counted once per Agent System. Knowledge-base indexing and storage is charged from upload while indexed data is retained. Storage and FDE services are excluded from subscription ARR. Usage is postpaid; subscriptions are prepaid. Taxes extra; inference included. One conditional planning case, not contracted revenue. Full assumptions: olbrain.com/fps-FPnA.
Win the first finance objective.
Earn the broader operating role.
Existing models and internal work
Keep the process within current tools and the finance team.
Specialist FP&A products
Buy a product optimized for the finance function.
Internal or platform-based builds
Assemble and maintain an agent system using available platforms.
Match the customer’s work
Recover the financial methods and assemble a system around a defined objective.
One platform across systems
Olbrain supports the first agent system and the systems that follow.
Accumulate deployment knowledge
Develop reusable methods, integrations and delivery playbooks as the customer base grows.
The competitive test is measurable finance value, deployment effort, total cost and paid expansion. Reuse and repeatability must be demonstrated.
Deployment depth is the commercial moat
we aim to build.
Self-identity helps earn trust to deploy. Each adopted agent system can deepen Olbrain’s role inside the enterprise.
Identity-bound operation
Agent mandates and signed action records give enterprises a way to inspect who acted and why.
Live foundation; full cryptographic exclusivity and continuity remain in development.
One OS across functions
More agent systems can accumulate workflows, integrations, operating history and governance on Olbrain.
Prove with sustained use, paid expansion and retention.
Deployment know-how
Reusable integration and control patterns can make the next similar enterprise faster to serve.
Prove with delivery time and margin. Customer data remains isolated.
A team built for agent systems
and enterprise deployment
Alok Gotam
IIM Ahmedabad. Co-founded Hotify, an AutoML company acquired by Sonasoft. Experience in machine agency and autonomous systems.
Leads product strategy and enterprise go-to-market.
Nishant Singh
IIT Kanpur. Experience in population-scale identity systems and published fingerprint-recognition research. Animal-AI Olympics category winner, 2019.
Leads platform engineering and system architecture.
Engineers and deployment staff work with customers to develop and operate agent systems.
₹2.4 Cr to agentify one enterprise
over a 12-month programme
Earn trust
Reproduce the finance team's current forecast and validate the first system.
Agentify functions
Expand deeper into FP&A and across business workflows.
Customer ownership
Enable its team to add and refine further systems on Olbrain.
₹52L transferred · ₹1.88 Cr remaining
₹3L ready, untransferred.
Previous round: ₹2.6 Cr · March 2025 · ₹50 Cr post-money.
₹75 Cr floor · ₹125 Cr cap
15% discount (0–12 months) · 20% (12–18 months)
40% product · 25% deployments · 20% commercial
10% compliance · 5% operations