If you make and move things, how can AI solve problems for you?  

We believe that the best results for AI in the physical world come from orchestrated, well-engineered composite multi-agent systems. Our goal is to empower you to build intelligent autonomous multi-agent systems for million-dollar industrial processes.

‍TRUE STORY:
From 6 Months to 72 Hours A manufacturer used large and complex machines that needed to be calibrated between runs of different products. The 10,000-step calibration process was so detailed that the company had only one senior operator who could do it – and it took him 6 months of tedious work each time a changeover was needed. Working with the operator, our team trained an intelligent autonomous agent to perform the calibration. A few months after the project kicked off, the agent was certified as an expert operator that could perform the months-long calibration in 72 hours – saving the company millions and giving back the operator months of his working life to devote to higher-level tasks.

Here's a tip for first steps.

Look for the following characteristics to identify where your AI agent(s) will make the biggest impact:

It’s a high-value, high-risk process in the physical world. Think of your most business-critical machines and processes. The best use cases for intelligent autonomous agents are processes and problems where performance improvements drive big business value.

It’s never been automated. Can you think of key parts of your processes and systems that automation has never been able to address? Intelligent autonomous agents can successfully automate tasks that have never been automated before.  

It requires human decision-making. Look for the parts of a process that only expert operators can run – the things that don’t get done if senior operators get sick or go on vacation. Intelligent autonomous agents can learn the complex, nuanced decision-making skills your organization depends on.