Pre-v1.0 Beta — Cognithor is under active development. APIs may change between releases. Not recommended for production customer-facing deployments. Bug reports and feedback welcome via Issues.
While the test suite is extensive (17,000+ test functions, 89% coverage gate), the project has not been battle-tested in production environments. Expect rough edges, breaking changes between versions, and some German-language strings in system prompts and error messages. See Status & Maturity for details. For non-technical users, wait until version 1.0.0 for stable long-term support.
Vibe-Engineered, not vibe-coded. Cognithor is not a weekend hack held together by AI-generated spaghetti. Every module follows a deliberate architecture (PGE-Trinity, 6-phase gateway init, 3-layer security, TRUST-1..10 operational-trust stack), backed by 17,000+ test functions, structured plans, spec compliance reviews, and code quality gates. The AI writes the code — but a human engineers the system. There's a difference.
Why Cognithor?
Most AI assistants send your data to the cloud. Cognithor runs entirely on your machine — with Ollama or LM Studio, no API keys required. Cloud providers are optional, not mandatory.
It replaces a patchwork of tools with one integrated system: 17 channels, 141 MCP tools across 30 modules, 6-tier memory with 4-channel hybrid search, knowledge vault, voice, browser automation, Computer Use, cross-platform social listening, signed audit receipts (TRUST-1..10), resumable batch workflows (CRWE), TUF-Light-signed pack registry, and more — all wired together from day one. The test suite is extensive (17,000+ test functions, 89% coverage gate). See Status & Maturity for what that does and does not guarantee.
In plain terms: Cognithor is an AI assistant that lives entirely on your computer. You talk to it through your terminal, a web UI, Telegram, Discord, or any of 18 supported channels — and it talks back, remembers what you said last week, and acts on your behalf. It can search the web, write and edit files, run shell commands, control your browser, automate your desktop (clicking, typing, reading windows), manage your calendar, and learn new skills over time. Think of it as a local, private, self-improving Jarvis.
Unlike cloud-based assistants, Cognithor keeps all your data on your machine. Your conversations, memories, documents, and credentials never leave your hardware unless you explicitly configure a cloud LLM provider. It works fully offline with Ollama or LM Studio, and it encrypts everything at rest with SQLCipher (AES-256). If privacy matters to you — and it should — this is the architecture you want.
What makes it different from other local AI tools is that Cognithor is not just a chatbot. It is an agent operating system: it plans multi-step tasks, evaluates its own results, learns from mistakes, and improves autonomously. It can control your desktop through Computer Use (screenshots, clicks, keystrokes, window automation), compete in ARC-AGI-3 reasoning benchmarks, and manage a marketplace of community-contributed skills. It is built to grow with you.
Status & Maturity
Cognithor is Beta / Experimental software. It is under rapid, active development.
| Aspect | Status |
|---|---|
| Core agent loop (PGE) | Stable — well-tested and functional |
| Memory system | Stable — 6-tier architecture works reliably |
| CLI channel | Stable — primary development interface |
| Flutter Command Center | Beta — Sci-Fi aesthetic, cross-platform, GEPA pipeline visualization, Robot Office pathfinding, 20+ config pages, chat, voice, learning dashboard |
| Messaging channels (Telegram, Discord, etc.) | Beta — basic flows work, edge cases may break |
| Voice mode / TTS | Alpha — experimental, hardware-dependent |
| Browser automation | Stable — Playwright-based, CAPTCHA solving, stealth mode |
| Computer Use | Stable — 6 phases (Vision, Agent Loop, Planner Intelligence, Security, Robustness, UI Automation) |
| ARC-AGI-3 Benchmark | Beta — 13/25 games solved (24 levels), 4 solver families incl. SmartExplorer |
| Skill Marketplace | Stable — GitHub registry, 5-check validation, publisher verification |
| Windows UI Automation | Beta — pywinauto UIA for exact element coordinates |
| Deployment (Docker, bare-metal) | Beta — tested on limited configurations |
| SSH Remote Execution | Beta — tested against Docker containers, key-based auth |
| Evolution Engine | Stable — all 6 phases complete, autonomous deep learning with quality self-examination, GDPR-compliant |
| Autonomous Task Framework | Beta — task decomposition, self-evaluation, recurring scheduling |
| Background Process Manager | Beta — 6 MCP tools, 5-method ProcessMonitor, SQLite persistence |
| Multi-Agent System | Beta — 5 specialized agents with model/temperature/top_p overrides |
| Audit & Compliance | Beta — HMAC + Ed25519 signatures, RFC 3161 TSA, GDPR Art. 15/33, WORM-ready, hash-chained prev_hash over canonical NFC-JSON, dedicated AuditCategory.REFLECTION channel for autonomous learning (Compliance-Spring v0.98.0) |
| Resilient Workflow Engine (CRWE) | Stable — cognithor task <manifest> with JSONL streaming, atomic checkpoint, file-lock, SIGINT/SIGTERM emergency-checkpoint between tasks, manifest-tamper detection on --resume, audit-chain integration. Crash-recovery integration test passes on Windows under SIGKILL (v0.99.0). |
| Pack Registry Signing | Beta — TUF-Light Ed25519 (offline Root + online Targets) + SHA-256 verifier; marketplace dormant by default until owner mints Root keypair |
| Video Composition & Rendering | Beta — cognithor.video package with pluggable RendererABC; default HyperFrames backend (Apache-2.0); 5 MCP tools (video_compose GREEN, video_render ORANGE, raw HTML RED at Gatekeeper); render-receipt linked to TRUST-1 via run_id; composer prompts + skill templates ship in cognithor.video.skills |
| Enterprise features (GDPR, A2A, Governance) | Stable — GDPR 100% user rights, consent management, SQLCipher encryption, audit trail |
| Encryption at Rest | Stable — SQLCipher (AES-256) for all databases, Fernet for files, OS Keyring key management |
| Cross-Platform Social Listening | Beta — Reddit + Hacker News + Discord scanning, LLM-scored leads, unified MCP tools |
| Hierarchical Document Reasoning | Beta — Tree-based retrieval for PDF/DOCX/HTML/Markdown, LLM-navigated section selection |
| CAG Layer (Cache-Augmented Generation) | Beta — Deterministic prefix generation for LLM KV-cache reuse, prefix + native builders |
| CLI Config TUI | Stable — Interactive terminal config editor (rich + prompt_toolkit), model discovery |
| AST-Based Security | Stable — Python AST + bashlex shell analysis replacing regex-based guards |
| OSINT / HIM Module | Beta — person/project/org investigation with trust scoring |
| Observer Audit Layer | Stable — post-response LLM quality check across 4 dimensions (hallucinations, sycophancy, laziness, tool-ignorance); triggers regeneration or full PGE re-loop; fails open |
What the test suite covers: Unit tests, integration tests, property-based tests (Hypothesis), audit-completeness burn-ins (nightly CI), real-life scenario tests, and live Ollama tests for all modules. The 17,000+ test functions verify code correctness in controlled environments.
What the test suite does NOT cover: Real-world deployment scenarios, net