Explainable Governance for AI-Driven Operations
Turn automated decisions into deterministic, human-reviewable receipts — before trust breaks.
Mindplane sits in the execution path of automated work and records every decision as it happens — intent, context, validation, and outcome — collapsing ambiguity at the source and reducing the surface area of operational and governance failures.
Where Mindplane Fits — and Why It Reduces Problems
Mindplane runs between intent and execution — not a policy engine, and not an after-the-fact log.
Systems submit intent. Mindplane evaluates and records the decision path. Execution may proceed — but the decision is never opaque.
Most operational failures don't start with bad intent — they start with ambiguity.
Traditional systems reconstruct decisions after the fact using logs, metrics, traces, and assumptions. Mindplane removes that reconstruction step by capturing the decision as it happens.
- Fewer places to look when something goes wrong
- Fewer interpretations of "what happened"
- Fewer hidden branches in automated systems
Think of Mindplane as a control-plane witness for automated work.
What you get in V1
V1 is focused on explainability and audit. It does not block actions — it makes them legible.
Deterministic Decision Receipts
Every run records intent, context, validator results, and outcome.
Validator Results + Reason Codes
Policy, safety, and branch validators return pass / warn / fail / halt.
Hash-Chained Trust Ledger
Append-only, tamper-evident. Every entry links cryptographically.
Inspection Surface
Query runs via API or Console. See why each decision was made.
GitHub Executor
Create pull requests with full decision provenance.
Slack Notifications
Decision summaries with risk markers and inspection links.
How it works
Five deterministic steps from intent to audit trail.
Intent Captured
The request is received with actor, intent, and risk signals.
Context Assembled
Correlation ID, tenant, environment, and plan are attached.
Validators Run
Policy, safety, and branch validators return pass / warn / fail / halt.
Arbiter Decides
Returns allow or deny with reason code based on validator results.
Receipt Written
The run is written to the Trust Ledger. Queryable by RunID.
Why it matters
SRE / Platform Teams
Know exactly what happened — without reconstructing it later.
AI / ML Teams
Deploy agents with governance in the execution path, not after.
Ops Managers
Answer "what happened and why" with tamper-evident records.
Architecture
Three layers from raw signals to immutable audit.
Signals
Raw events from webhooks, APIs, and monitoring. Tagged with correlation IDs.
Runs
Context assembly, validator chain, Arbiter decision. The governance path.
Trust Ledger
Append-only, hash-chained. Immutable and tamper-evident.
Integrations
Available in V1
Webhooks and signal ingestion provide context and intent, not enforcement. They allow Mindplane to explain why an action happened — even if it originated elsewhere.
- GitHub (executor + webhooks)
- Slack (notifications)
- Prometheus / Alertmanager
- REST API
Planned (V2+)
- Jira (executor)
- ServiceNow
- Microsoft Teams
- Datadog / CloudWatch
Security & Trust
Tamper-Evident Hash Chain
SHA-256 links each entry. Modification breaks the chain.
Append-Only Ledger
Entries cannot be deleted. Denied runs are also recorded.
Multi-Tenant Isolation
Enforced at API boundaries, not application logic.
Audit-Ready Records
Every decision is queryable and explainable.
How V1 Evolves into V2
V1 establishes deterministic, auditable decision records.
V2 builds enforcement on the same substrate — without changing the trust model.
What changes in V2
- Decisions can block or require approval
- Limits become enforceable, not advisory
- Multi-agent dispute workflows
What does not change
- The receipt format
- The Trust Ledger
- The validator and Arbiter model
V1 is about seeing clearly.
V2 is about acting safely — using the same evidence.
Early Access — V1
We're onboarding teams building or operating autonomous systems.
V1 focuses on visibility and audit. Enforcement arrives in V2+.
The Team
Scott Alexander
Founder & CEO
SRE leader, 10+ years building scalable infrastructure.
Jay Kinder
Co-Founder & CTO
Principal SRE, automation and platform engineering.
Contact
