The product
Five operating surfaces over one company graph: people, delivery, revenue, customers and knowledge. Each team gets the surface its work needs; all of them read and write the same facts, and governed agents operate across every one.
A suite integrates separate products after the fact. An OS models the company once and puts surfaces on top. That is why capacity in Delivery already knows about leave in People, and why a promise in Revenue is traceable to the work that keeps it.
People
Leave, attendance, comp-off accrual, onboarding, payroll, policy and announcements over one org graph, so capacity is a fact the rest of the OS can read.
Delivery
Projects, epics, work items, sprints, boards and velocity are how delivery is stored, not a plugin bolted onto a ticket tracker.
Revenue
Accounts, deals, stages, forecast and demos sit beside the projects that fulfil them, so a promise made in a deal is traceable to the work that keeps it.
Customers
Customer conversations arriving by email or ticket become one Customer Problem with an owner, a commitment and a verified resolution.
Knowledge
Policies, product facts, decision records and runbooks form the grounding layer every answer and every agent reasons from.
An HR system records who took leave. A tracker records that a ticket closed. A CRM records that a deal moved. OmniManas records the causal chain between them: what was needed, what the company changed, and whether the outcome was proven.
Commitments, decisions and context survive handoffs, reorganizations and tool changes.
A signal is interpreted against people, customers, rules, software, production reality and history.
Every affected team sees the same change, its owner and what must happen next.
Outcomes return to the operating model, improving the next brief, forecast and action.
Because the surfaces share a graph, an agent gains context from all of them and acts inside the permissions of the person it is working for. Sensitive decisions stay human-owned on every surface.
People
Resolve leave and policy questions from the actual policy, move stalled approvals along and surface payroll or capacity anomalies before a cycle closes.
Employment decisions stay human
Delivery
Generate stories from intent, groom the backlog, propose a sprint against real capacity and flag the dependency that will slip before the standup does.
A person commits the sprint
Revenue
Research accounts, qualify signals, draft outreach within approved claims and keep pipeline state current instead of asking a rep to.
Pricing and legal route to people
Customers
Investigate against rules, code and production behavior, prepare the change, coordinate approval and confirm the customer outcome.
Review before anything ships
Knowledge
Detect where documentation, business rules and real behavior have drifted apart, and propose the update rather than answering from a stale page.
Owners approve every change
A customer report is the work that touches the most surfaces at once: conversation, commitment, delivery plan, code, release and production behavior. It is the clearest test of whether one graph actually pays off.
Customer signal
The report, affected account and export sample are linked to the weekly reconciliation commitment.
Conversation · account · export
Investigation
Ledger rules, product documentation, the export path and production traces isolate the divergence and blast radius.
Rules · code · traces
Governed change
The change, regression test, affected customers and reviewer policy travel together in one Change Passport.
Patch · tests · owner
Release
CI, rollout state and export telemetry remain attached to the same resolution—not a separate incident timeline.
CI · deploy · telemetry
Verified outcome
Production evidence and customer confirmation close the commitment and become outcome-labelled memory.
Behavior · confirmation · memory
Observe
Events from work and systems
Understand
Meaning resolved in context
Decide
Options ranked with evidence
Act
People and agents execute
Learn
Outcomes return to memory
The loop is the same on every surface: understand intent and reality, make a governed change through accountable owners, verify the result, and retain the evidence.
See the architecture behind the loop →