Summit Trails' founders wanted to eliminate manual implementation work and costly custom integrations by having AI observe work directly from screenshots.
Supervisors would only trust the data at 98% accuracy or better, and target customers in credit unions, insurance, and healthcare demanded that no PII or PHI ever leave their environment. The team needed to know whether those constraints were technically feasible before funding a build.
DevDash Labs ran a four-week feasibility study for Summit Trails, a stealth-mode operations consultancy, designing a visual-intelligence platform on local Visual Language Models inside the client's private cloud. Dual agentic workflows pushed screen-reading accuracy toward 98%, with an optional cloud validation layer, across a design spanning eight integrated systems.
The four-week study confirmed that 98% screen-reading accuracy, the trust threshold supervisors required, was achievable.
Three independent CIOs signed off on the zero-image-to-cloud, privacy-first architecture designed for regulated industries.
DevDash delivered a de-risked, three-phase 20-week build plan with Go/No-Go gates spanning eight integrated systems.
- How Jewelbench Cut Jewelry CAD Modeling Time by 95%Ideas2IT Technologies · Manufacturing & Industrial
- How Superintelligent Interviewed 150 Staff for $500 With AIFractional AI · Technology & Software
- How Walmart Cut 18 Weeks From Fashion Design-to-ShelfHuman Machines Group LLC · Retail & E-Commerce
- How a Legal Tech Firm Won Back 7-Figure ARRBonsai Labs · Legal & Compliance