Epistemic Memory API
Governed store/query/update/relate operations with explicit revision discipline and scoped mutation paths.
Governed Epistemic Substrate for Enterprise AI
Noesis provides deterministic, revision-bound epistemic state transitions across AI systems. It governs memory mutation, provenance, and replay so organizations can reconstruct what a system believed at decision time and under which policy constraints. Deploy it self-hosted as a control layer between models, agents, and stateful memory. The enterprise package includes a database-backed memory layer (PostgreSQL + pgvector) with bootstrap scripts to provision schema and migrations on installation.
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Independent Proof Pack (No Source Code)
Download the latest evidence bundle containing governance block/rollback demo logs, release evidence artifacts, pgvector bootstrap dry-run output, targeted memory/epistemic/federation test results, and SHA256 checksums.
Memory Database Included
Ships with database-backed memory support (PostgreSQL + pgvector), plus install-time bootstrap for schema and migrations.
Provenance Chain
Every memory transition carries provenance metadata and policy context for tamper-evident auditability.
Snapshot & Replay
Supports snapshot controls and deterministic replay for decision-time state reconstruction.
Policy-Bound Mutation
No silent belief mutation. State changes require explicit auditable operations with governance hooks.
Multi-Agent Coherence
Shared truth substrate and governance discipline for multiple agents without epistemic fragmentation.
Governance-First Architecture
Noesis is not a UI shell; it is the policy and epistemic integrity substrate beneath interaction layers.
Compliance Fit
Designed for regulated and high-accountability environments requiring traceability and replayability.
Enterprise Deployment
Self-hosted middleware for organizations that need auditable AI memory operations under internal control.