The Platform

18 services across 5 intelligence layers and 4 hardening domains.

15 Modules Canonical REV3 architecture
18 Services Cognition to release
16 API Endpoints Cognition fabric surface
33+ Schemas Shared MCP contract
REV3 ARCHITECTURE

The canonical REV3 architecture organizes the factory into 5 explicit layers. Advisory intelligence is always subordinate to the authoritative control plane. No advisory module may replace governance.

1. Architecture & Documentation
/docs, /architecture

Frozen baseline, ADRs, diagrams, repository conventions

2. Authoritative Control Plane
/control-plane, /governance, /schemas

Authoritative state, policy, task contracts, evidence, release authority

3. Advisory Intelligence
/planning-engine, /autonomy-safety, /work-generation, /economic-intelligence, /organizational-ai, /factory-learning, /opportunity-engine

Recommendations, safety, planning, economics, learning — all subordinate to control plane

4. Operator Surfaces
/ui, /execution-agents

Control Tower, Dashboard, bounded execution workers

5. Runtime Support
/telemetry, /simulation, /scripts, /infra, /tests

Observability, scenario testing, deployment, verification

COGNITION FABRIC

The foundational intelligence layer. Every advisory service depends on the cognition fabric for knowledge retrieval, inference tracking, and retrieval trace auditing.

CognitionContextStore

12 knowledge source kinds — specs, decisions, risks, postmortems, policies, tasks, evidence, architecture, release, governance, learning, economic

ArtifactIndexRegistry

19 discovery rules scanning docs, operations, readiness, policy-packs, and test artifacts with freshness tracking and stale detection

InferenceLedger

SHA-256 input/output hashing, token counting, latency tracking, model lineage refs for every AI invocation

RetrievalTraceLedger

Session context, rerank basis, strategy tracking (semantic/keyword/hybrid), result persistence

CognitionEngine

Embed → rerank → search pipeline with pluggable mock/live mode and RTX 3090 integration

PLANNING INTELLIGENCE

Planning Memory

Analog retrieval from past project outcomes with confidence scoring and source refs

Scenario Planning

3 strategies generated per scope — aggressive, balanced, conservative — with risk calibration

Plan Comparison

7-dimension component diff: sprints, effort, risk, capacity, critical path, dependencies, tasks

Effort Estimation

Complexity-based estimation from lines changed, files touched, tests, schema changes

Plan Calibration

30% weighted prior adjustment from estimated-vs-actual outcome deltas

Sprint Composition

Priority-sorted capacity fitting with utilization tracking and risk posture

ECONOMIC INTELLIGENCE

Cost Attribution

Per-task and per-program cost tracking across 6 categories: execution, verification, coordination, rework, infrastructure, governance

Cost-of-Delay

Urgency scoring with delay impact classification (LOW/MEDIUM/HIGH/CRITICAL) and portfolio ranking effects

Program ROI

Risk-adjusted return, marginal utility scoring, payback sprint estimation

Economic Forecast

Forecast-vs-actual variance tracking with OVER/UNDER/MATCH direction detection

Exception Handling

Auto-escalation for BLOCK severity, resolution workflow with actor/note tracking

ORGANIZATIONAL AI

Capability Graph

Actor profiles (human/agent/team/service) with skill taxonomy and availability tracking

Skill Matching

Coverage scoring and gap detection — NONE/PARTIAL/MISSING severity per required skill

Bottleneck Prediction

Queue saturation detection from review load — NONE/EMERGING/ACTIVE/CRITICAL severity

Load Balancing

Overload/underload detection with transfer suggestions across actors

Coordination Risk

Cross-project shared actor/resource conflict detection with auto-escalation for CRITICAL

FACTORY LEARNING

Learning Corpus

7 source kinds ingested: postmortem, closeout, evidence, alert, incident, decision, forecast error

Pattern Mining

Tag-based recurring failure detection with support count and LOW/MEDIUM/HIGH confidence

Policy Recommendation

Advisory policy deltas with evidence lineage — PROPOSED/ACCEPTED/REJECTED/EXPIRED lifecycle

Estimation Calibration

Prior adjustment from real outcomes with sample size tracking

Lesson Promotion

CANDIDATE → PROMOTED → ACTIVE → RETIRED lifecycle with max-age retention policy

HARDENING

Execution

Incident records, lineage manifests, override receipts (RECOVERY/BREAK_GLASS/ADMIN_CORRECTION), dispatch replay

Governance

Exception records (TEMPORARY/EMERGENCY/TRANSITIONAL/WAIVER), policy bundles, completeness scoring, debt tracking

Release

Strategy advisory, cohort analytics, runbook quality scoring with drift detection

Compliance

Coverage mapping, waiver risk analysis, continuous posture scoring, evidence lineage with tamper detection

TECHNOLOGY
React + Vite Frontend (HOME-PRO)
Fastify + Zod BFF Layer
Python + FastAPI Backend Services
PostgreSQL Database
TypeScript Factory Scaffold (15 modules)
RTX 3090 Local Inference
Docker Compose Deployment (HOME-PRO)
Kubernetes Deployment (Enterprise)

See it in action

18 services. 5 intelligence layers. 10/10 maturity.