We built Inspec-Ther after seeing how solar inspections still depend heavily on manual review, fragmented tools, and time-consuming analysis of thermal and visual data. The challenge wasn’t simply detecting anomalies, it was turning raw inspection imagery into something operators could actually act on. We wanted to identify defects at panel level, classify them consistently, understand their severity, and connect each finding back to the physical solar asset. Along the way, Inspec-Ther evolved from a detection tool into a more complete inspection intelligence platform. We’ve been working on thermal analysis, computer vision, defect classification, geospatial mapping, dataset verification, model training, and structured reporting — with the goal of creating a traceable workflow from drone capture → AI analysis → human verification → maintenance decision. We’re launching Inspec-Ther because we believe solar inspections should become faster, more measurable, and increasingly automated as solar infrastructure continues to scale. We’d love feedback from solar operators, asset owners, engineers, drone inspection teams, and anyone working in renewable energy. What part of the solar inspection workflow do you think needs the most improvement today?

Inspec‑Ther

AI-powered thermal intelligence for solar inspections

AI-powered thermal intelligence for solar inspections