A shared memory, attribution & governance layer for AI coding agents. Not an orchestrator — a blackboard.
Observe: standalone, governed, auditable intake and normalization — raw external events into trusted, canonical, immutable observations.
Project Memory — organizational, causal memory for AI teams. Ask why, not just what.
Governed LinkedIn marketing over MCP — draft, review, publish, comment, and AI-write (Anthropic/OpenAI/Gemini) via the official LinkedIn API. MCP server + CLI.
The shared Evidence primitive for the Octopus stack — canonical, hashable, tamper-evident evidence that flows between repos.
Octoryn Web Ingestion Engine: governed, auditable, AI-native web/PDF ingestion
Standalone governed execution runtime: trigger to result across autonomy, policy, approval, connector, execution, and audit boundaries.
Catch governance holes before production does. A static governance linter for AI agent workspaces.
One-click remote dev/ops platform — browser VS Code + 5 AI CLIs + Octopus Blackboard, as an AWS/Azure Marketplace image.
Make every incident byte-for-byte reproducible. A determinism harness for governed event streams.
The governed work-state layer: a task is a verifiable provenance chain, not a to-do.
Add a description, image, and links to the octoryn topic page so that developers can more easily learn about it.
To associate your repository with the octoryn topic, visit your repo's landing page and select "manage topics."