Local-first shared memory and coordination layer for AI coding agents, with repository evidence, reservations, handoffs, code graph context, and dashboard review backed by PostgreSQL/pgvector.
A coordination layer for coding agents that provides memorable identities, inbox/outbox messaging, searchable message history, and file lease management to prevent conflicts. Uses Git for human-auditable artifacts and SQLite for fast queries, enabling multiple agents to collaborate across projects without stepping on each other.
A production-grade coordination hub that enables AI agents and human teams to work as a single organism by sharing tasks, context, decisions, and persistent memory across projects. It features two-tier agentic memory with per-agent hot caches, inter-agent messaging, and multi-agent authorship tracking for seamless collaboration.
Local-first memory engine for AI-agent teams: private/team/project ACL, associative recall, and federated sync across nodes. One SQLite file, no LLM required.
A shared memory and coordination layer for AI coding agents that provides a tamper-evident timeline, conflict awareness, and attribution for multi-agent coding workflows.
A durable multi-agent orchestrator for software development with explicit run graphs, checkpoint/resume capabilities, and project memory exposed through MCP resources and tools. It enables coordinated agent workflows for coding, review, repair, CI, and approval with SQLite-backed memory retrieval and pluggable research backends.