Industrial engineers who build multi-agent AI systems are becoming superheroes.
AMESA is built by engineers for engineers in industry. It’s a platform designed to strengthen your ability to build more, get results faster, and solve problems that your organization has never been able to solve before. You’re the expert and you need to be free to do what you do best . . . even better.
Machine Teaching & Gerardo for the Win

Gerardo [name changed for anonymity], is a process engineer for a national flat-rolled steel producer. When Gerardo learned about machine teaching and the engineering methodology for agentic AI, he knew he could use it to achieve huge process improvements in his steel manufacturing business.
Using machine teaching principles, his engineering ingenuity, and subject matter expertise, Gerardo created a multi-agent system that lowered maintenance and operations costs, improved quality and delivery of products, and improved quality of life for the shop personnel – generating two million dollars in ROI in the first year alone.
#superhero feels appropriate
Adam and his Multi-Agent System for the Win

Adam [name changed for anonymity], a chemical engineer, was the only expert operator certified to execute a 10,000-step calibration on a high-density polyethylene production machine. Every calibration took him approximately 6 months, taking his time away from running other important processes and oversight in his company. Knowing he needed to find a more efficient solution, Adam knew built a multi-agent system that successfully completed the 6-month, 10,000-step calibration process in 72 hours.
#needlesstosay....superhero
AMESA makes it easy to build multi-agent systems using subject matter expertise and engineering skills without writing code. It’s a platform purpose-built to enable engineers to create multi-agent AI systems that solve the hardest automation challenges.
With the no-code Agent Builder Studio you can create well-engineered autonomous AI systems, train them in simulations of your processes, watch as your agents start beating benchmarks, and deploy the best performing agent designs to automate processes that could never be automated before.
That’s how you save the day and become an AI superhero – or at least get a promotion.
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If you make and move things, how can AI solve problems for you?




