Discuss your enterprise use case ↗
Olbrain / The Agent OS
Build, run and govern coordinated agent systems on Olbrain. Work with our deployment engineers today, or explore upcoming developer access through Claude or Codex with Alchemist.
Build, run and govern coordinated agent systems on Olbrain. Work with our deployment engineers today, or explore upcoming developer access through Claude or Codex with Alchemist.
Enterprise implementation available today. Developer access is upcoming.
Agent systems that work together
Clear responsibilities and handoffs.
Conceptual design. Each connection and expansion requires agreed scope, engineering and validation.
One operating layer / Two ways to build
Enterprise implementation today. A developer route in early access.
Work with Olbrain forward-deployed engineers (FDEs) to scope, build and validate agent systems for your enterprise. Your teams define the objective and retain oversight and control.
Explore enterprise implementation ↗Alchemist is the planned connection from your coding assistant to Olbrain Agent OS. An optional developer route to build, run and govern agent systems on the same operating layer.
Explore developer early access ↗01 / FP&A example
In this example, scope one FP&A workflow across the departments that supply its inputs. Agree the model, review steps and acceptance criteria before implementation.
Data sources, planning assumptions and financial model mapped.
Agreed P&L and management presentation outputs.
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
Inspect assumptions, review the impact and record the decision.
Data
A schematic planning workbook. Manual collection is a valid starting point.
Example sources selected to fit the business. Inventory may apply in other enterprises.
P&L
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
Revenue moves from $100.0m to $95.0m. Delivery costs rise $2.1m. With shared costs unchanged, operating profit falls $7.1m to $2.9m.
Prepared scenario summary. Finance reviews the assumptions and output before release.
Live questions
This public walkthrough uses an authored scenario.
Assumptions: revenue 100 × 0.95 = 95.0; total delivery costs 70 × 1.03 = 72.1; shared operating costs held at 20.0. Independent revenue and cost assumptions. Operating profit: 95 − 72.1 − 20 = 2.9 ($m).
Human review
Human review does not guarantee future forecast accuracy.
Decision record
The generated summary supports the decision. A person approves the decision.
Fictional, industry-neutral data. An authored workflow illustration, not a customer result, live product capture or forecast.
03 / Implementation journey
Your teams define the business context. Olbrain FDEs implement the agreed system on Olbrain Agent OS.
Map the business objective, source data, cadence, owners, approvals and constraints.
Your business team + IT + OlbrainDefine outputs, success checks, responsibilities, dependencies and commercial structure.
Joint agreementImplement on Agent OS. Begin with approved data access; integrations depend on agreed scope.
Olbrain FDEs + your IT teamReconcile agreed outputs, test scenarios, review access and confirm sign-off criteria.
Your reviewers + OlbrainAgree operating responsibilities, review cadence, support and the next expansion decision.
Joint rollout and ownership04 / Enterprise expansion
Choose each system against your business priorities. An FP&A system illustrates how a validated scope could connect to the departments that shape a forecast; it is one possible path on Olbrain.
Example upstream P&L drivers / selected to fit your business
Revenue, demand and pipeline
Capacity, staffing and utilization
Supplier costs and purchasing
Stock and working capital, where relevant
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
Specialized agent systems work toward business-wide goals and constraints, with relevant shared context, clear responsibilities and handoffs, and common governance. Each deployment defines what context may be shared, who owns each decision, when work passes between systems, and where human approval is required.
These connections are designed and validated for each deployment. A shared platform alone does not establish coordination, complete action capture or enterprise-wide learning. Workflow design is configurable; integrations, shared context, controls and cross-system behavior require engineering and validation within the agreed scope.
The aim is coordinated business outcomes: specialists carry out their responsibilities while handoffs and controls keep the wider business objective in view.
Hypothetical example: a proposed price reduction connects sales, finance, operations and customer service. Sales supplies the demand assumption; finance tests margin constraints; operations checks capacity; customer service reviews the customer promise. Named owners resolve conflicts and approve the decision before downstream action. This illustrates a workflow to configure and validate, not a shipped autonomous pricing capability or a customer result.
An identity-bound, signed, append-only record supports attribution of recorded agent actions.
Define each agent's mandate, access and human approval steps in the agreed implementation scope.
Agree the source versions, assumptions and review evidence needed to inspect the work and accept an output.
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
Agentifying your enterprise means progressively turning its work into connected agent systems. Build, run and govern on Olbrain, with optional human workspaces where review, decisions or action are needed.
Build the agent system.
Open Olbrain ↗Run and govern the system.
Open runtime workspace ↗Add a human interface when needed.
Explore workspaces ↗Headless systems do not require Screens. Read the technical context ↗
07 / Implementation and ownership
Your business team defines the objective 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 (TMB) is the supporting vision: complementary connected intelligence and a coherent customer experience as governed systems work together. It is a long-term ambition developed through scoped deployments, with people retaining judgment and accountability. Connected systems and records alone do not establish enterprise-wide learning; TMB is not a separate product or a shipped enterprise-wide capability.
Read the thinking behind The Machine Brain ↗Your first deployment
Explore an illustrative FP&A workflow, then discuss your business objective, review process and rollout dependencies.
Discuss your enterprise use case ↗