Multi-agent flows with reviewable hand-offs
Multi-Agent Team Orchestration
14 orchestration strategies for teams of AI agents. From governed agent teams to structured pipelines - agents collaborate, compare outputs, and escalate uncertain work for review.
Key Capabilities
Governed Swarm Orchestration
Agents claim tasks under coordinator rules, policy gates, and operator-visible logs before results move forward.
Planner-Executor Pipeline
One agent decomposes the problem into subtasks. Worker agents execute in parallel and fan results back to a convergence point.
Competitive Racing
Multiple agents race to solve the same task. The fastest valid result wins - ideal for search, retrieval, and optimization problems.
Self-Critique Loops
An agent reviews and revises its own output through iterative refinement loops until a quality threshold is met.
Human-in-the-Loop Gates
Insert approval checkpoints at any stage. Agents pause execution and wait for human review before proceeding.
Dynamic Team Composition
Teams are assembled at runtime based on task requirements. Add, remove, or swap agents without redeploying the workflow.
How It Works
Define Agents
Create specialized agents with distinct roles, tools, and system prompts. Each agent focuses on one part of the task.
Choose Strategy
Select from 14 orchestration strategies - sequential pipeline, parallel fan-out, swarm, debate, voting, and more.
Set Guardrails
Apply per-agent guardrails, approval gates, and quality thresholds. Control autonomy at every step.
Deploy & Monitor
Run the team as a single flow. Observe each agent's decisions, costs, and latency in real time.
Technical Stack
Ready to build production
Self-host in minutes with Docker, or use the cloud. Either way, you own your data and your models.