IMA-AI is my personal multi-agent AI platform: a supervisor named IMA that knows you, remembers and delegates tasks to specialised agent teams. Local-first and able to run on your own machine.
Three roles in one interface:
- Personal assistant: IMA organises everyday life & work and delegates to specialist teams.
- AI Workflow Studio: visual automations from building blocks, manually or AI-generated.
- Dev / coding tool: agent teams build software, run code and deploy projects.
How it works
One message becomes a plan: the intent router decides whether IMA answers itself or hands off to a team. A team lead breaks the request into board tasks with dependencies, a board executor runs them as a DAG in parallel, a review pipeline (code + security review) checks each result, and a synthesis pass merges the parts into one coherent result, streamed live back into the chat.
Highlights
- Agentic loop: agents reason, call tools and work in multiple steps (up to 12 iterations).
- Kanban board: autonomous task execution with a review pipeline (planned → in_progress → review → done).
- Workflow engine: visual node editor (~17 node types) with cron scheduling and an AI generator.
- Teams & agents: supervisor → team leads → sub-agents, model configurable per agent.
- Workspace sandbox: sandboxed file system + whitelisted command runner with a live terminal.
- Deploy via Coolify: from project to build & live URL via GitHub push (auto-HTTPS).
- Memory with provenance: facts with provenance and scopes (global/private/work/project).
- Token & cost tracking: usage per agent, daily budget with a fallback model.
Technically a TypeScript monorepo (Turborepo + pnpm): a Fastify 5 backend with built-in node:sqlite (FTS5), a React 19 frontend, LLM access via OpenRouter (plus Gemini and local serving via Ollama). In active development, the core loop works.