AMESA provides an Intelligence Engineering Platform for designing, training, and deploying intelligent agents for enterprise optimization. The platform allows engineers to configure multi-agent systems using a no-code interface and secure simulation-driven training environments. This orchestration of expertise and data enables scalable deployment of production-ready agents to drive autonomy across industrial operations.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises with complex, high‑value physical processes lack a practical way to translate expert operator knowledge into reliable automation, resulting in reliance on manual intervention, limited scalability, and missed efficiency gains. Traditional AI tools often require extensive coding and cannot safely test agents in realistic operational environments before deployment.
Solution
AMESA delivers an Intelligence Engineering Platform that lets engineers build, train, and deploy multi‑agent AI systems without writing code. A drag‑and‑drop Orchestration Studio lets users define agent hierarchies, goals, and constraints, while the secure Agent Cloud provides a simulation‑driven proving ground that integrates digital twins and synthetic data for safe, iterative learning. The platform’s machine‑teaching methodology captures subject‑matter expertise and converts it into reusable agent skills, enabling continuous improvement through feedback loops. Built‑in visual debugging, benchmarking, and assist‑agent guidance accelerate development cycles and ensure performance meets operational standards. Once validated, agents are deployed at scale across enterprise systems with direct human‑agent collaboration interfaces. The end‑to‑end workflow unifies design, training, validation, and production, turning institutional knowledge into measurable autonomy.
Target Audience
The platform targets engineering and data‑science teams in large‑scale industrial enterprises—such as manufacturing, energy, chemicals, aerospace, logistics, and automotive—who need to automate high‑risk, knowledge‑intensive processes.
Features
- No‑code Agent Orchestration Studio with drag‑and‑drop workflow builder and hierarchical team visualization
- Simulation‑driven training environment (Agent Cloud) that connects to digital twins, PLC data streams, and synthetic datasets for safe experimentation
- Machine‑Teaching framework that encodes expert operator decisions into reusable agent policies and skills
- Visual debugging and benchmarking dashboards for real‑time performance monitoring and iterative refinement
- Assist agents that provide guided configuration, human‑in‑the‑loop oversight, and continuous learning updates
- Scalable deployment pipeline with API and SDK integration for ERP, MES, and control‑system connectivity
- Role‑based access control and end‑to‑end encryption for secure multi‑tenant operation