Welcome to Composabl
Composabl is the platform for creating industrial-strength multi-agent AI systems that make high-impact decisions in the real world.
With Composabl, you can convert expert knowledge about how a process works into a team of agents with specialized skills that work together to allow the system to make the right decision in every situation. These can be either programmed or learned through advanced AI techniques and orchestrated so that the multi-agent system performs effectively in every part of the process and under any conditions. For skill agents that learn by practicing, Composabl trains the agent systems in realistic scenarios until the agent system can succeed at the task and outperform the alternatives.
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Integrate with Composabl
You can use any model or Python algorithm with Composabl for training agent systems, adding perception, analysis, and communication, and making decisions. See how to configure different types of modules in the UI and by publishing them via the data science workflow for agent system design, training, and deployment.
Integrate a machine learning model
Use existing ML models for machine vision, prediction, or analysis in Composabl agent systems
Integrate a language model
Set up an LLM call to add communication to your agent system
Integrate a programmed algorithm
Configure any Python algorithm, such as a PID controller or optimization algorithm, as a skill agent in Composabl
Integrate third-party software
Use an API call to external software as a skill agent in Composabl
Integrate a simulator
Configure your simulator to work with Composabl
Publish to the platform
Upload configured models and algorithms to the Composabl UI with one CLI command
Create Modular Skill Agents
Composabl multi-agent systems are built on modular skills that break down a task into separate parts. Learn how to create skill agents to train with deep reinforcement learning.
Create skill agents with goals and constraints
Create skills agents with subject matter expertise by configuring goals and constraints for learning
Create skill agents with rewards using the SDK
Create skill agents that learn with rewards and access additional teaching tools in Python
Publish to the platform
Upload skill agents configured with the SDK to the Composabl UI for training and deployment
Deploy Multi-Agent Systems
Once Composabl agentic systems are designed and trained, you can export them to the Composabl runtime to connect with your system. Learn how to deploy an agent within the runtime container and how to use Composabl's tools to analyze agent behavior during both training and deployment.
Evaluate the performance of your multi-agent system
Evaluate performance using the Composabl benchmarking feature
Deploy a Composabl multi-agent system
Export a multi-agent system and connect to the Composabl runtime container
Connect the multi-agent system to your production system
Connect the Composabl runtime container to your system for deployment
Audit multi-agent system behavior with the historian
Use the Composabl historian to analyze system behavior in detail
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