Engineering Intelligence Platform
Transform engineering activity into clear, actionable, business-readable intelligence.
Cogence automatically analyzes signals from software development teams and converts them into concise reports that help non-technical leaders understand what engineering accomplished, what's happening, and what requires attention.
Engineering teams create enormous amounts of information daily through commits, deployments, pull requests, and discussions. Yet most non-technical leaders cannot easily understand this information, creating a gap between those building software and those making business decisions.
Cogence bridges that gap by continuously analyzing engineering signals and generating business-readable reports that answer:
- What did engineering accomplish?
- What are teams working on?
- Where are risks emerging?
- What should leadership know?
The pilot focuses on one question: "What did we do during the last 24 hours?"
Data Sources: Gitea repositories and Git commits only
Delivery: REST API + Rocket.Chat at 21:00 Asia/Tehran (no dashboard)
Output: Daily business-readable report with:
- Executive summary
- Active repositories
- Contributor activities
- Management notes
See MVP v1 Documentation and Product Slices for build order.
- Vision - Why Cogence exists
- Principles - Core design principles
- Requirements - Functional requirements
- Target Users - Who we're building for
- User Stories (Pilot) - MVP v1 pilot scope
- Backlog - Deferred stories and features
- Glossary - Key terminology
- MVP v1 - Pilot specification
- Product Slices - Vertical build plan
- System Overview - High-level architecture
- Domain Model - Core entities
- Data Model - PostgreSQL schema
- Data Flow - Processing flows
- Setup Guide - Development environment setup
- Contributing - How to contribute
- Git Conventions - Commit message format
- Testing Strategy - Testing approach
- API Reference - REST API documentation
- ADR-001 - Commits as source of truth
- ADR-002 - Business language in reports
- ADR-003 - No code analysis in MVP
- ADR-004 - Signals over surveillance
- ADR-005 - AI generates summaries
- ADR-006 - Daily report first
- ADR-007 - Human readability priority
- ADR-008 - Single-tenant approach
- ADR-009 - FastAPI backend choice
- ADR-010 - PostgreSQL as system of record
- ADR-011 - Scheduled data collection
- Backend: FastAPI (Python)
- Database: PostgreSQL
- Data Source: Gitea API
- AI: LLM for report generation
- Delivery: REST API + Rocket.Chat
- Deployment: Single-tenant, internal-first
- Business First - Reports for managers, not engineers
- Signals Over Surveillance - Understand work, don't monitor people
- Context Before Metrics - Explain what happened, not just numbers
- Explainability Over Mystery - Transparent AI summaries
- Human-Centered Reporting - Readable in under 60 seconds
🚧 In Development — MVP v1 Pilot
Current focus: Product Slice 1 — collect commits from Gitea.
See LICENSE file for details.
We welcome contributions! Please read CONTRIBUTING.md for guidelines.
For questions or issues, please open a GitHub issue.