A central business-intent layer for autonomous agents.
Principia translates executive direction into signed, grounded, and replayable mandates — using your business knowledge graph to bind intent to AI Agents across vendors, domains, and tool calls.
Authority outruns control.
Agents may already log their own reasoning. But self-narration isn't proof of accountability to a mandate — it's a plausible story after the fact.
Principia binds each decision to a versioned mandate, traceable back to the executive intent behind it.
Intent has to bind across vendors.
A company runs a fleet — revenue from one vendor, support from another, internal agents besides. "How our business should run" is expressed per-vendor, inconsistently, or nowhere.
Principia is a neutral mandate layer that directs every agent from a single, central source of business intent grounded in your knowledge graph.
A business-intent mandate layer, alongside the agents already in production.
Intent, grounded in your business knowledge graph.
A business owner writes intent in plain language. Principia translates it through the company's knowledge graph — a semantic model of its concepts, domains, relationships, decisions, and history — and composes a domain-specific mandate per agent (domain × role × capability).
"Eligible for a retention discount" resolves to the concrete fields and tools of that agent's domain — but not as a flat mapping. Principia separates the strategic levers an executive can pull from the hard boundaries that must never bend: segment, churn_score, discount_pct, margin_floor.
- Structural grounding through the knowledge graph, not keyword retrieval
- Multi-Tier Rule Resolution: natively separates dynamic executive goals (Permissions and Priorities) from unalterable operational boundaries (Prohibitions and Guardrails)
- Served over MCP, or enforced at the tool call
- Same central intent serves agents from any vendor
Every decision is bound to a signed mandate — and replayable.
Run a candidate mandate over the last N real decisions and see exactly which would change before it ships.
12% of decisions would have changed outcome.
Compare mandate versions against history before they go live.
LLM at authoring time. Deterministic at runtime.
The LLM is confined to authoring time — translating natural language into a grounded predicate against the business knowledge graph, signed off by a human.
Runtime is deterministic: a pure function of (domain, role, capability), cached, with no model in the request path.
To save the pattern-match.
Principia sits near several familiar categories. It isn't any of them.
Live Regulatory Enforcement. Instead of checking compliance boxes after the fact, Principia compiles corporate regulations directly into the agent's bounding box at configuration time, hard-stopping violations before they ever reach an API.
Intent is grounded through the knowledge graph to real fields and replayed against history — not keyword-matched against policy documents.
The agents a company already ships stay in place. Principia directs them; it doesn't replace them.
Agents can already narrate why they acted. Principia records each decision's accountability to a versioned mandate — provable and replayable, not a plausible story.
Build the mandate layer with us.
We are working with a small number of companies that run autonomous agents in production and need a single, provable way to bind them to business intent. If that is you, let's talk.
Book a Discovery CallOr email us directly at hello@principiaos.com