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Σ OVERWATCH — Institutional Decision Infrastructure for coherence, credibility, and drift governance

Project description

CI PyPI License: MIT Python 3.10+ Release

Σ OVERWATCH

Current pilot release: v2.0.3
See: docs/release/RELEASE_NOTES_v2.0.3.md

Institutional Decision Infrastructure

Trust layer for agentic AI: verify before act, seal what happened, detect drift, ship patches.


What It Does

Organizations make thousands of decisions. Almost none are structurally recorded with their reasoning, evidence, or assumptions. When leaders leave, conditions change, or AI accelerates decisions 100x — governance fails silently.

Σ OVERWATCH fills this gap with three primitives:

  • Truth — Decision Ledger Records (DLR) capture what was decided, by whom, with what evidence
  • Reasoning — Reasoning Scaffolds (RS) capture why — claims, counter-claims, weights
  • Memory — Decision Scaffolds + Memory Graphs (DS + MG) make institutional knowledge queryable

When assumptions decay, Drift fires. When drift exceeds tolerance, a Patch corrects it. This is the Drift → Patch loop — continuous self-correction.


Quick Start

pip install deepsigma

# Health check
deepsigma doctor

# Score coherence (0–100, A–F)
python -m coherence_ops score ./coherence_ops/examples/sample_episodes.json --json

# Drift → Patch in 60 seconds
python -m coherence_ops.examples.drift_patch_cycle

# Full 7-step Golden Path (no credentials needed)
deepsigma golden-path sharepoint \
  --fixture src/demos/golden_path/fixtures/sharepoint_small --clean

Court-Grade Proof (60 seconds)

# Seal + sign + authority bind + transparency log + pack
python src/tools/reconstruct/seal_and_prove.py \
    --decision-id DEC-001 --clock 2026-02-21T00:00:00Z \
    --sign-algo hmac --sign-key-id ds-dev --sign-key "$KEY" \
    --auto-authority --pack-dir /tmp/pack

# Verify everything in one command:
python src/tools/reconstruct/verify_pack.py --pack /tmp/pack --key "$KEY"

Key Capabilities

Capability Description Docs
Coherence Ops CLI Score, audit, query, reconcile decision artifacts CLI Reference
Golden Path 7-step end-to-end proof loop Golden Path
Credibility Engine Institutional-scale claim lattice with formal scoring Engine Docs
Trust Scorecard Measurable SLOs from every Golden Path run Spec
Excel-first BOOT Govern decisions in a shared workbook — no code required BOOT Protocol
MDPT Multi-Dimensional Prompt Toolkit for governed prompt ops MDPT Docs
Court-Grade Admissibility Seal-and-prove pipeline: Merkle commitments, transparency log, multi-sig witness, hardware key hooks Admissibility Levels
MCP Server Model Context Protocol server with auth + rate limiting MCP Adapter
RDF/SPARQL Semantic lattice queries via in-process SPARQL 1.1 SPARQL Service
Dashboard React dashboard with Trust Scorecard + Zustand store Dashboard

Connectors

All connectors conform to the Connector Contract v1.0.

Connector Transport Docs
SharePoint Graph API docs
Power Platform Dataverse Web API docs
AskSage REST API docs
Snowflake Cortex + SQL API docs
LangGraph LangChain Callback docs
OpenClaw WASM Sandbox docs
Local LLM llama.cpp / OpenAI-compatible docs

Repo Structure

DeepSigma/
├── src/                 # 12 Python packages (all source code)
│   ├── coherence_ops/   #   Core library + CLI
│   ├── engine/          #   Compression, degrade ladder, supervisor
│   ├── adapters/        #   MCP, SharePoint, Snowflake, LangGraph, OpenClaw, AskSage
│   ├── deepsigma/       #   Unified product CLI
│   ├── demos/           #   Golden Path, Excel-first Money Demo
│   ├── mdpt/            #   MDPT tools + Power App starter kit
│   └── ...              #   credibility_engine, services, mesh, governance, tenancy, verifiers, tools
├── tests/               # 1250+ tests, fixtures, datasets
├── docs/                # Documentation + examples (canonical, mermaid, lattices, etc.)
├── dashboard/           # React dashboard + API server
├── schemas/             # JSON schemas (core engine + Prompt OS)
├── artifacts/           # Workbooks, templates, sealed runs, sample data
├── prompts/             # Canonical prompts + Prompt OS control prompts
└── .github/             # CI/CD workflows

Documentation

START_HERE.md Front door
HERO_DEMO.md 5-minute hands-on walkthrough
NAV.md Full navigation index
ABOUT.md Reality Await Layer (RAL)
OPS_RUNBOOK.md Operations + incident playbooks
STABILITY.md Versioning policy + stability guarantees
docs/99-docs-map.md Complete docs map

Excel Prompt OS v2

Structured cognition workbook for institutional decision-making — no code required.

Prompts


Contributing

See CONTRIBUTING.md.

License

MIT


Σ OVERWATCH We don't sell agents. We sell the ability to trust them.

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