AtlasLLM
Thirty models.
One conversation.
A privacy-first, multi-model AI chat platform with agentic research. Deep Research and Pro Search modes built on a custom workflow engine.
AtlasLLM puts thirty-plus models from nine providers behind one conversation, routed through a single OpenRouter abstraction. Switch models mid-thread without losing context.
It is local-first by default; your data lives on-device, with optional real-time Convex sync across devices. Four chat modes, from a quick answer to multi-step Deep Research, all share the same streaming, reasoning-visible interface.
One router, four agentic flows.
A custom, type-safe workflow engine (@repo/orchestrator) runs each request as a graph of tasks, with dependencies, retries, timeouts and parallel fan-out. The router dispatches to one of four modes; Deep Research plans searches, runs them in parallel, and loops the reflector back to the planner until the answer is complete.
Calm on every screen.
Reasoning and web-search steps, inline sources and citations: the full research trail behind every answer.
Deep Research, fully responsive: steps, sources and the streamed report on a phone.
Nine providers, one API.
9 providers · 30+ models · 4 chat modes · 11 workflow tasks
AtlasLLM