hestiaOS Alpha is online.
Governance-first infrastructure for controlled agent execution.
hestiaOS evaluates, gates and traces agent actions before execution - with public evidence surfaces for implemented controls, limitations and human approval points. Built for teams that need auditability, replayability and trust boundaries before agents touch real systems.
This page documents what is implemented today, what is experimental, and where human approval remains required. Evidence before hype. Limitations before claims.
Demo
Watch controlled agent execution with evidence, gates and audit trail.
Demo video - 60s walkthrough
Architecture
hestiaOS operates on the concept of Layer 7.5 — a deterministic execution substrate between probabilistic AI reasoning and real-world effects.
AI Agent Space
Probabilistic, untrusted, volatile. Model inference remains upstream.
Deterministic Governance Substrate
DSGK, CEG, CausalTraceGraph, Moirai. Governed, auditable, replayable.
Application Space
Typed contracts, MCP tools, OS interfaces.
Why hestiaOS
Agents should not mutate systems from ungoverned knowledge states. HestiaOS separates what an agent knows from what it is allowed to do.
Knowledge before execution
Every knowledge state carries validation scores, evidence sources, and governance boundaries. Agents cannot act on unvalidated knowledge.
Proposal before mutation
Agents do not mutate systems directly. They propose. The governance kernel reviews. Only approved proposals reach execution.
Audit by design
Every action produces a causal trace - replayable under new policies. Trust is built on evidence, not architecture diagrams.
Public Evidence
Key verified results from the SPRIND Next Frontier AI submission. Each claim backed by tests, benchmarks, or code.
Deterministic Semantic Governance
Intent Lifecycle & Execution Gate
Non-Gradient Knowledge Accumulation
Containerized Reproducibility
Event-Sourced Vault · 10 Invariants
Governed vs. Ungoverned Baseline
Trust & Limitations
Trust is produced by evidence, not adjectives. This page documents current maturity — it is not a compliance claim.
✓ Implemented
DSGK constraint solver, CEG intent lifecycle (QUEUED → COMMITTED), CausalTraceGraph audit records, Moirai pattern reuse engine.
⚡ Experimental
Full integration pipeline, production deployment hardening, AI Act compliance tooling — under active validation.
👤 Human Approval Required
Critical actions are gated. Novel action patterns fall through to human review by design.
🔒 Security Assumptions
Pre-alpha validation environment. Production security hardening is a Stage 1 deliverable.
Brand Keywords
Core external keywords per hestiaOS Corporate Identity. Evidence-first, no hype claims.
Who should review this alpha
We are looking for critical feedback from people who understand the problem space.
🧠 AI governance researchers
Knowledge state governance, policy enforcement, safety-oriented runtime design.
⚙️ Agent infrastructure builders
Execution substrates, tool-use frameworks, MCP implementations, deterministic systems.
🏛️ Enterprise / public-sector architects
Regulated environments, controlled AI execution, auditability requirements.
🔗 Knowledge graph people
KGA, deontic knowledge graphs, evidence scoring, constraint ranking.
Give critical feedback
Alpha is online. No pitch deck attached. Just looking for serious critique.