Source & provenance
Identify the originating system, version, timestamps and supported fields before treating imported state as reliable.
Integrations
Connect AI context without losing its source.
AI systems, tool authority, evaluations and review records live across different platforms. Steerlane's integration model is designed to bring that information into a common assurance context while keeping provenance and unknowns visible.
Integration scope and availability are confirmed during evaluation; the journeys below are sample designs, not proof of deployed connectors.
Four boundary questions
Integration should increase confidence, not hide uncertainty.
Permission scope
Define which metadata and evidence may be accessed. A source connection alone does not establish effective authority.
Evidence freshness
Distinguish current observations, historical approvals, missing fields and evidence that may require revalidation.
Decision ownership
Source systems provide context; an explicit authorized reviewer remains responsible for the final governance decision.
Sample data
Inspect what a source can—and cannot—tell you.
Explore a simulated source inventory with explicit gaps in provenance and coverage.
STEERLANE / SOURCE INVENTORY / FUTURE ADAPTER DESIGN · SYNTHETIC
01 / Source inventory and provenance
Know the source, not just the agent name.
Select a hypothetical source to see declared state, its approved reference and what cannot yet be trusted.
No live discovery, OAuth, API polling, partner certification or customer connection is involved.
Agent configuration
Credit Policy Copilot
- Declared (example)
- Agent tools: credit_lookup; knowledge: policy_library
- Approved reference (example)
- Approved reference v2 · read-only credit lookup
- Proposed change
- Candidate tool scope: credit_lookup + document_lookup
- Provenance / freshness
- No authenticated import · authored fixture
Unverified effective state
Effective environment permissions, deployed model and last successful sync are unknown.
Compare the declared candidate against the approved reference before an authorized review.
Integration playbooks
Explore the contract behind each ecosystem.
Each playbook describes the desired source inputs, assurance questions and current evaluation boundaries. It does not represent a live connection.
Evaluation playbook
Microsoft Agent 365 + Copilot Studio
An architectural preview of how native Microsoft agent configuration and identity context could be normalized into a Steerlane assurance lifecycle.
Read integration scope ↗Evaluation playbookLangGraph + LangSmith
A proposed pathway from governance-relevant LangGraph topology and LangSmith evaluation evidence to Steerlane's dependency-aware assurance model.
Read integration scope ↗Evaluation playbookMCP shared capabilities
A sample cross-system scenario: connect a shared MCP capability to dependent systems, evidence and the next required review.
Read integration scope ↗Evaluation playbookServiceNow review coordination
A sample handoff design between Steerlane's required human review and a ServiceNow task; approval authority stays separate from ticket status.
Read integration scope ↗Evaluation playbookGitHub + Azure DevOps
How repository revision and change-request context could connect a declared AI configuration to a candidate, mapped assurance impact and a governance review.
Read integration scope ↗Cross-agent impact
A shared tool change can affect more than one system.
Trace a sample dependency from a shared MCP capability into the systems and evidence that may need review.
Cross-agent change intelligence
Shared Customer Records MCP
Stage 1 of 5: AI estate.
Import and normalize
Different agent stacks, one governed perspective.
Three fictional agents share an MCP capability. A qualified integration would retain native provenance, source freshness and explicit unsupported fields before mapping a dependency.
Copilot Studio / Agent 365
Customer Support Agent
Shared dependency: Customer Records MCP
Illustrative source only
LangGraph / LangSmith
Claims Review Agent
Shared dependency: Customer Records MCP
Illustrative source only
Custom / MCP
Research Assistant
Shared dependency: Customer Records MCP
Illustrative source only
All agents, controls and results are fictional · No live vendors or decisions
Start with the systems you actually use.
We scope supported fields, access boundaries and required integration work before proposing a pilot.