Composabl enables autonomous agent-driven automation in industrial operations
Composabl Platform empowers companies in industrial manufacturing, logistics, energy, and aerospace to deploy real-time autonomous AI agents to automate complex processes previously managed solely by human experts. Users can leverage a no-code orchestration studio and a Python SDK to build, train, and deploy AI agents that interact directly with factory floor systems such as SCADA, MES, HMI, and ERP. Using simulation-based machine teaching, expert operators embed their knowledge into agents, ensuring human-aligned, explainable, and safe automation outcomes. The system is designed for modularity, adaptability, and transparency, allowing for seamless integration of custom algorithms and LLMs. Major use cases include glass bottle manufacturing (operator logic automation via HMI), logistics scheduling (robust multi-agent scheduling for a Fortune 50 logistics company), oil & gas (virtual operator agents for a Fortune 10 energy giant), and aerospace (population simulation for a global aircraft manufacturer). By digitizing and scaling human expertise, Composabl achieves reliability, scalability, and reduced human dependency. The platform uses Microsoft AI infrastructure and SDKs for seamless orchestration and scalable enterprise deployments. Key platform capabilities include a no-code UI and advanced SDK, simulation-based training, integration with existing industrial systems, explainable and modulable agent behavior, and real-time deployment in physical environments. Composabl supports rapid prototyping and operationalizing of AI-driven autosystems for diverse industrial applications, enhancing operational efficiency and preserving critical expert knowledge.
- Organization
- Glass Bottle Manufacturing
- Industry
- Manufacturing
- Location
- Global
Reported outcomes
Strategic outcomes
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Glass Bottle Manufacturing, A global aircraft manufacturer
- Provider
- Microsoft
- Maturity
- Production
- Linked source
- AppSource
Composabl supports rapid prototyping and operationalizing of AI-driven autosystems for diverse industrial applications, enhancing operational efficiency and preserving critical expert knowledge
Primary read
Use case focus
Showing 3 of 4
- 1Autonomous Agent-Based Manufacturing Process Automation
- 2AI-Driven Logistics Scheduling and Optimization
- 3Virtual Operator Programs for Oil & Gas
- Automating traditionally human-driven, high-value and safety-critical industrial processes.
- Managing skill shortages and knowledge transfer as expert operators retire or leave.
- Maintaining operational reliability despite complex, real-time physical environments.
- Improving throughput and scheduling robustness in logistics amid staffing variabilities.
- Scaling human expertise across diverse environments and sectors.
- Deployment of AI autonomous agents using Composabl's no-code orchestration studio and Python SDK.
- Simulation-based machine teaching with expert operator knowledge embedding into AI agents.
- Integration of agents with industrial control systems (SCADA, MES, HMI, ERP) for real-time operation.
- Modular and explainable multi-agent system design for adaptability and scalability.
- Use of Microsoft AI infrastructure and SDKs for enterprise-grade integration and deployment.
- Automated real-time decision-making in glass manufacturing, logistics, energy, and aerospace.
- Preserved and scaled human expertise, reducing knowledge loss risk.
- Increased operational reliability and reduced reliance on scarce expert labor.
- Improved resilience and throughput in logistics scheduling despite staffing gaps.
- Enabled flexible, modular adaptations for new and evolving use cases.
Architecture
AI agents are constructed and orchestrated in a no-code studio or through a Python SDK. Agents are trained and validated within simulated environments using 'machine teaching' with embedded human expertise. Upon deployment, these agents connect to, and operate in, real-world industrial environments by interfacing directly with SCADA, MES, HMI, and ERP systems for control and monitoring. The system supports integration of various models (LLMs, RL agents, proprietary code), and ensures modularity, transparency, and adaptability.
Sources & evidence2
- Customer explicitly identified
- Deployment status explicitly supported
- Technical implementation details available
- Multiple corroborating sources available
AI-generated summary. Verify important details with the linked sources before relying on this case.
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