The Circuit aims to unite the IT Community around finding, developing and funding solutions that move the needle for business. With more and more hype surrounding the proliferation of enterprise AI, technology leaders are hard pressed to separate signal from noise. That’s why we are presenting this program.
Unlock up to $100,000 in funding to transform your business with AI! The Circuit invites Cincinnati’s leading companies to submit their innovative AI use cases for a chance to develop a proof of concept with top industry experts. Selected projects will receive expert consultation, substantial financial support, and public recognition. Submit your AI vision today and be a part of driving technological innovation in our community!
Proving Ground 2024 Use Case Results:
“Through the vision of The Circuit leadership and the establishment of The Proving Ground Project, PL Marketing, an employee-owned company specializing in retail merchandising services, collaborated with AMEND Consulting, a leader in AI delivery, to create several truly innovative and usable AI tools for image processing. This pilot led to a solution that, at scale, will likely save PLM over 10,000 labor hours annually and make data significantly more accessible.”
RHAero worked with partner CoStrategix to develop an AI Proof of Concept (POC) after winning The Circuit’s Proving Ground program. The POC would enhance RH Aero’s operational efficiency with intelligent document processing efficiency. In the first two weeks alone, the AI Agent returned an accuracy rate of 95% and saved 25% of the hours engineers spend on the document sanitization process. In the long term, however, the benefits are likely to be significantly greater.
Proving Ground 2025 Use Case Results:
“Through the vision of The Circuit leadership and the establishment of The Proving Ground Project, Qualtronics, a Corterra Group
Company specializing in custom wire harness design, collaborated with AMEND Consulting, a leader in AI delivery, to deliver an
innovative tool streamlining the inbound customer service requests and order processing.”
“The goal was to build a Machine Learning (ML) model into RAF Vue that could automatically identify which patient records were most likely to contain coding errors. By flagging high-risk charts, UASI could move from manual, broad-spectrum auditing to a targeted, high-impact approach.”