Govern AI-driven engineering before it turns into risk.
AI agents generate code.
Your organization still owns the consequences.
Asplenz Knowledge gives your agents a structured decision layer - so they don't guess.
AI velocity changed. Governance didn't.
AI-assisted development is becoming default in many teams.
Agents now:
- introduce dependencies
- modify APIs
- refactor architecture
- deploy infrastructure
But they don't know:
- your architectural decisions
- your non-negotiable security invariants
- which exceptions were approved
- what must never change
Without a declared decision layer, agents guess.
Asplenz Knowledge
Operational Decision Governance for AI Systems
Knowledge is a declarative system of record for:
Agents query this normative state before acting.
Knowledge does not block execution; it exposes the applicable decision state. Your ecosystem decides.
MCP-native (Model Context Protocol compatible). Built for modern AI coding environments and CI pipelines.
Explore KnowledgeFrom declaration to enforcement
Declaring rules is not enough.
Knowledge Verifier (Premium Add-on)
Knowledge Verifier analyzes every Pull Request against your declared normative state.
It:
- Resolves applicable scope
- Detects invariant and rule violations
- Validates override usage
- Enforces Implementation Report citations
- Produces a CI-ready verdict (pass | warn | fail)
- Generates a human-readable Compliance Report
You choose the mode:
- Report-only
- Fail on blocking violations
- Strict (citation enforced)
What operational governance looks like
Instead of:
"We think this change is fine."
You get:
Every merge becomes explicitly evaluated against declared constraints.
No tribal knowledge. No invisible assumptions.
Who this is for
- Engineering teams using AI coding tools
- Organizations introducing autonomous agents
- Platform & security teams defining invariants
- CTOs who want velocity without architectural drift
Different by design
Knowledge is not:
- A code quality scanner like SonarQube
- A vulnerability scanner
- A generic policy engine like Open Policy Agent
- A prompt
Those tools evaluate code or execute rules. Knowledge structures the decisions themselves.
It governs:
- Why a rule exists
- Who approved an exception
- What replaced what
- Which constraints are non-negotiable
It operates at the normative layer.
A note on Evidence
Asplenz also builds Evidence - an independent product for sealing high-stakes decisions and generating cryptographically verifiable proof artifacts.
Evidence addresses a different layer of governance: immutable proof for critical commitments.
Start free with the AI Registry. Inventory your AI systems, classify them under the EU AI Act, and see where your proof gaps are - at no cost.
Human-readable. System-executable.
Engineers can:
- Retrieve past decisions and rationale
- See when and why a rule changed
- Understand approved exceptions
CI pipelines can:
- Evaluate PRs against invariants
- Validate overrides
- Produce structured verdicts
Agents can:
- Query applicable rules before acting
One normative state. Used by humans and systems.
Start governing decisions at AI speed
Agents act.
Organizations remain accountable.
Asplenz Knowledge makes that sustainable.