The engine for reliable, stateful agent collaboration. Powered by the AgentControlLayer platform, we enable your agents to work together seamlessly.
Orchestrate any agent framework
Build complex multi-agent systems without the complexity. We handle coordination, state management, and handoffs.
Design multi-agent workflows visually. Drag, drop, connect. No code required for orchestration logic.
Multi-agent systems need shared context. Our state layer ensures agents have the information they need, when they need it.
When one agent finishes, another begins. Seamless handoffs with typed contracts and validation at every transition.
Event-driven architecture for agents. Publish events like "UserSignedUp" and let any agent subscribe and react asynchronously.
Getting two agents to work together is easy. Getting ten agents to work together reliably is an engineering nightmare.
Ad-hoc coordination logic scattered across services. No single source of truth for how agents interact.
Who has the latest context? What happened three steps ago? Without proper state management, multi-agent systems become unpredictable.
When a 5-agent workflow fails at step 3, you need to know why. Traditional debugging tools don't help with distributed AI.
Multi-agent systems need multi-level support. We partner with you from design to production.
We analyze your current workflows and identify the highest-ROI opportunities for agentic automation.
Our architects build your agents on the AgentControlLayer platform, ensuring security and scalability.
We deploy to production and train your team on how to manage the Human-in-the-Loop approval flows.
We stay on as your AgentOps partner, reviewing logs and optimizing prompts weekly to prevent drift.
We focus on teams who already ship or operate agents and now need a proper AgentOps control plane.
Product and platform teams adding agents into their SaaS products—support bots, onboarding agents, lead routing, and other embedded workflows.
Central teams that support multiple agent use cases across the business and need one place to control prompts, policies, and observability.
Shops that build agents and workflows for clients and want to offer them as reliable, audited services instead of one-off scripts.
Under the hood, AgentControlLayer is a full AgentOps control plane: a workflow engine, agent identity system, and observability layer that treat agents as first-class principals.
A LangGraph-powered workflow engine with schema-based IO, support for multi-agent patterns, and built-in Human-in-the-Loop nodes so you can pause, review, and resume critical steps.
Agents are treated as their own principals with permissions, histories, and versions—not just prompts in code. This aligns with emerging best practices from Google/Kaggle and others.
Designed to support Promptsmith-style atomic prompt boxes and AI-assisted reviews of prompts and workflows so you can continuously improve quality without losing control.
Common questions about coordinating multi-agent systems.
Supervisor, Pipeline, Hierarchical, Debate/Consensus, and Swarm patterns. Choose the pattern that fits your use case, or combine them for complex workflows.
Agents read and write to a shared state store with conflict resolution. State is versioned and can be rolled back. Agents can subscribe to state changes for reactive workflows.
Yes. The Orchestration Dashboard shows real-time workflow execution: which agents are active, what state they're reading, where bottlenecks are occurring, and full execution traces.
Define retry policies, fallback agents, and compensation actions at each step. AgentOrchestrationLayer handles failure propagation and recovery automatically.
One AgentOps control plane to build, secure, and observe your agent fleet.
Stop pasting strings into code. Our visual Prompt Builder UI allows you to design, test, and version complex prompts with variables, conditional logic, and model comparisons side-by-side.
Treat agents as first-class citizens with their own IAM roles. Manage permissions, enforce budget limits, and maintain complete audit trails of every decision your AI makes.
Bring DevOps discipline to LLMs. Version control your entire agent configuration—workflows, prompts, and RAG settings. Implement Human-in-the-Loop (HITL) checkpoints before critical actions.
Ready to deploy agents that actually work? We are accepting a limited number of enterprise clients for our Managed Agent Program. Get a custom roadmap, a dedicated AI Architect, and access to the AgentControlLayer platform.