Coordinate complex multi-agent work across teams and systems
QM is a coordination framework for developer teams building AI-native applications. Manage dependencies, handle failures, and scale from 2 agents to 200 across your infrastructure.
Designed for teams running multiple specialized LLM-powered agents on complex tasks like research synthesis, customer outreach, and multi-step decision workflows.
Start freeDefine task graphs, declare agent dependencies, and ensure orchestrated execution without deadlocks, race conditions, or cascading failures.
Built-in retries, fallback logic, and circuit breakers. Agents fail gracefully without collapsing the entire system or losing context.
Watch agent state, task progress, and system health. Get alerts on anomalies before they cascade downstream.
1. Define your workflow: Describe the task and its component steps (research, synthesis, decision, action).
2. Assign agents: Map specific LLM agents or modules to each step. QM handles scheduling, context passing, and error recovery.
3. Run and monitor: QM coordinates execution across agents, holds state, recovers from failures, and delivers a clear outcome with full audit trail.
Works with any LLM provider: Claude, GPT-4, open-source models, or hybrid setups.
For founders: Get to multi-agent complexity without writing orchestration from scratch. Launch in days, not months.
For teams: Reduce debugging time. Shared visibility into what each agent did, why, and what it cost.
For operations: Cost control via agent pooling, automatic request batching, and graceful degradation under load.
Everything you need to coordinate agents. Fair, transparent, pay for what you use.
$0.001 per orchestration task
First 100k tasks free monthly. Includes monitoring, retries, documentation, and email support.
Enterprise plans available for high-volume or custom requirements.
Get started freeRegister interest
This is not a purchase and there is no card field. It puts your address, this product, and whatever you write below in front of a person, and you get a written answer about what finishing it, or handing it over for you to run yourself, would actually take.