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Composabl

Composabl provides a platform for engineers to build intelligent autonomous agents by integrating technologies such as Deep Reinforcement Learning and Machine Learning using modular building blocks. This enables organizations to automate complex industrial processes without requiring extensive coding skills, enhancing operational efficiency and reducing reliance on software developers.

San Francisco, United StatesFounded 2023121K+ followers
Updated 20 months ago

Funding

$5.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

Product

Problem

Many industrial processes rely on manually tuned algorithms, requiring extensive software development and specialized expertise to automate effectively. The lack of accessible tools prevents process engineers from directly leveraging their domain knowledge to build and deploy intelligent automation solutions.

Solution

Composabl provides a no-code platform that empowers process engineers to build and deploy autonomous agents for industrial automation. The platform allows users to orchestrate multiple technologies, including deep reinforcement learning, machine learning, and mathematical algorithms, using a drag-and-drop interface. By leveraging a machine-teaching methodology, engineers can train AI agents to make real-time decisions for complex cyber-physical systems without extensive coding. The platform enables the creation of intelligent agents that can optimize processes, reduce energy consumption, improve throughput, and enhance product quality.

Target Audience

The primary target audience includes process engineers, industrial automation system integrators, and manufacturing companies seeking to automate complex industrial processes and optimize operational efficiency.

Features

  • No-code UI for building and training autonomous agents
  • Support for integrating diverse technologies, including deep reinforcement learning, machine learning, and mathematical algorithms
  • Machine-teaching methodology for breaking down complex tasks into manageable skills
  • Building blocks for creating composite skills from algorithms, heuristics, AI models, and computer vision models
  • Tools for orchestrating skills in sequences or hierarchies
  • Python SDK for creating intelligent agents
This profile is AI-generated and may contain inaccuracies.