Inputs + model
Data sources, planning assumptions and financial model mapped.
Olbrain Agent OS / Enterprise adoption
Agentify your
enterprise.
Start with FP&A.
For large enterprises with recurring forecasts built from inputs across departments. Adopt Olbrain Agent OS, beginning with an FP&A system implemented by Olbrain forward-deployed engineers (FDEs) alongside your finance and IT teams.
For large enterprises with recurring, cross-department forecasts. Adopt Olbrain Agent OS, starting with an FP&A system implemented by Olbrain forward-deployed engineers (FDEs) with finance and IT.
A scoped enterprise implementation. No sign-up required.
Your enterprise agent systems
01 / First deployment
FP&A
Model. Forecast. Review. Decide.
↓ Validate, then expand
Proposed expansion
Upstream financial drivers
↓ Scope the next system
Enterprise destination
Broader enterprise functions
Solid: first deployment. Dashed: proposed expansion after validation.
Built on Olbrain Agent OS
Implemented with Olbrain FDEs
Expanded through validated scope
01 / First deployment
A recurring forecast.
A clear first deployment.
Scope one FP&A workflow across the departments that supply its inputs. Agree the model, review steps and acceptance criteria before implementation.
Forecast outputs
Agreed P&L and management presentation outputs.
Review + decisions
Human review steps and a decision record defined.
Initial data collection may be manual. Integrations are scoped against your systems. Outputs are tied to an agreed model, input set and review workflow.
02 / Illustrative demo
See how your enterprise moves from inputs to decisions.
Inspect assumptions, review the impact and record the decision.
Data
Planning inputs, with context.
A schematic planning workbook. Manual collection is a valid starting point.
Sales outlook
Owner: Sales · Version: v1
Assumption status: ready for review
Workforce / resource plan
Owner: People + operations · Version: v1
Assumption status: ready for review
Supplier cost plan
Owner: Procurement · Version: v1
Assumption status: ready for review
Example sources selected to fit the business. Inventory may apply in other enterprises.
P&L
Make the movement visible.
$m
Baseline
Scenario
Change
Revenue
100.0
95.0
−5.0
Delivery costs
70.0
72.1
+2.1
Shared operating costs
20.0
20.0
0.0
Operating profit
10.0
2.9
−7.1
Assumptions: revenue 100 × 0.95 = 95.0; total delivery costs 70 × 1.03 = 72.1; shared operating costs held at 20.0. Independent revenue and cost assumptions. Operating profit: 95 − 72.1 − 20 = 2.9 ($m).
Presentation
A draft for management review.
Draft · not approved
Revenue pressure and higher delivery costs reduce operating profit.
Revenue moves from $100.0m to $95.0m. Delivery costs rise $2.1m. With shared costs unchanged, operating profit falls $7.1m to $2.9m.
Prepared scenario summary. Finance reviews the assumptions and output before release.
Live questions
Ask a controlled scenario question.
This public walkthrough uses an authored scenario.
Operating profit becomes $2.9m, down $7.1m.
Assumptions: revenue 100 × 0.95 = 95.0; total delivery costs 70 × 1.03 = 72.1; shared operating costs held at 20.0. Independent revenue and cost assumptions. Operating profit: 95 − 72.1 − 20 = 2.9 ($m).
Human review
Finance reviews before deciding.
Review checklist · illustrative
- Input versions and source owners checked
- Model logic and independent assumptions checked
- P&L reconciled against the agreed model
- Exceptions reviewed before approval
Human review does not guarantee future forecast accuracy.
Decision record
Keep the decision distinct from the draft.
- Scenario
- Revenue −5%; delivery costs +3%
- Decision
- Accept this scenario for planning discussion
- Rationale
- Review revenue exposure and delivery capacity before committing resources
- Owner
- Finance lead (illustrative)
- Review status
- Human-approved scenario · illustrative record
The generated summary supports the decision. A person approves the decision.
Step 1 of 6
Fictional, industry-neutral data. An authored workflow illustration, not a customer result, live product capture or forecast.
03 / Implementation journey
Map the work. Validate the system.
Then deploy.
Your teams define the business context. Olbrain FDEs implement the agreed system on Olbrain Agent OS.
01
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02
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03
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04
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05
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Map finance, inputs and controls
Map the planning model, source data, cadence, owners, approvals and constraints.
Finance + IT + OlbrainAgree scope, acceptance and pricing
Define outputs, success checks, responsibilities, dependencies and commercial structure.
Joint agreementBuild and integrate the system
Implement on Agent OS. Begin with approved data access; integrations depend on agreed scope.
Olbrain FDEs + your IT teamValidate with finance and IT
Reconcile agreed outputs, test scenarios, review access and confirm sign-off criteria.
Your reviewers + OlbrainDeploy the approved scope
Agree operating responsibilities, review cadence, support and the next expansion decision.
Joint rollout and ownership04 / Enterprise expansion
From the P&L outward.
Start with FP&A. Extend into the departments that shape the forecast, then apply the platform to further enterprise workflows.
Example upstream P&L drivers / selected to fit your business
Sales
Revenue, demand and pipeline
Workforce + resource planning
Capacity, staffing and utilization
Procurement
Supplier costs and purchasing
Inventory
Stock and working capital, where relevant
↓ Example driver relationships
First deployment / financial decision system
FP&A: model, forecast, review, decide
↓ Validate readiness and agree scope
Then expand across enterprise functions
Choose each workflow against business priority, dependencies and validated readiness.
Phased rollout concept. Select applicable drivers; these are not mandatory modules or claims of live connector availability. Each expansion is a separate scoped decision with its own dependencies and acceptance.
05 / One operating layer
Each system contributes.
The enterprise comes together.
Shared context, continuing agent identities and attributable actions are the foundation for systems that contribute to the enterprise as a whole. Agent OS brings workflow state, memory and an identity-bound record onto one operating layer. As you expand, agree what context each system can use, which decisions require review and how its work connects to the next system.
Who acted?
An identity-bound, signed, append-only record supports attribution of recorded agent actions.
Under what authority?
Define each agent's mandate, access and human approval steps in the agreed implementation scope.
What informed the decision?
Agree the source versions, assumptions and review evidence needed to inspect the work and accept an output.
How do corrections carry forward?
Define how accepted corrections update the working context and reviewed outputs, with responsibilities and checks agreed for the system.
The signed-record foundation is live. Complete cryptographic enforcement of identity exclusivity and narrative continuity remains in development. Preserved identity and records alone do not establish enterprise-wide learning.
06 / Platform
One Agent OS. Three clear roles.
Studio
Build the agent system.
Explore Studio ↗Noesis
Run and govern the system.
Explore Noesis ↗Screens
Add a human interface when needed.
Explore Screens ↗Headless systems do not require Screens. Read the technical context ↗
07 / Implementation and ownership
Your team owns the business model.
Olbrain FDEs implement the system.
Finance defines the model and accepts the outputs. IT enables access and technical approvals. Olbrain FDEs implement on Agent OS and work through validation with both teams. The enterprise retains accountability for its agents and their actions; decisions requiring human judgment or authorization remain with your people.
08 / Long-term vision
The Machine Brain.
Your enterprise's cognition, made coherent.
The long-term ambition is to bring the enterprise's existing knowledge, memory, decisions and learning into a coherent whole. Progressively building governed systems on one operating layer is the path toward that ambition, with people retaining judgment, authorization and accountability.
The Machine Brain is a long-term vision, not a claim of a shipped enterprise-wide capability. Connecting systems and preserving their records does not, by itself, demonstrate enterprise-wide learning.
Read the thinking behind The Machine Brain ↗Your first deployment
See how your FP&A
system could work.
Walk through an illustrative enterprise workflow, then discuss your models, review process and rollout dependencies.
Book an FP&A demo ↗