
Every semester, engineering students waste hours in electronics labs debugging simple wiring mistakes, while overstretched teaching assistants can't reach everyone. Around 70% of "it's not working" requests turn out to be avoidable errors like a reversed LED or a missing ground connection. CIRIS solves this. Students select their lab exercise, upload 1–4 photos of their real breadboard from different angles, and receive instant, specific wiring feedback — what's wrong, why, and how to fix it. CIRIS is powered by AI/ML API using a two-step pipeline: GPT-4o analyzes the circuit images against the correct reference wiring, then GPT-4o-mini structures the output into reliable JSON for the interface. It offers two modes — Structured Lab Exercises for high-accuracy reference-based diagnosis, and Free Analysis for any custom circuit. Built entirely with native.builder (React frontend) and Supabase (auth, database, storage, Edge Functions), CIRIS is a real computer-vision product, not a chatbot wrapper — turning a simple phone photo into actionable engineering feedback.
10 Aug 2026

CLARIS AI is an end-to-end explainable multimodal video captioning system designed to generate accurate, natural, and context-aware captions from short video clips. It combines visual scene understanding, speech recognition, OCR, motion analysis, and multimodal AI reasoning to build a unified understanding of a video before generating four distinct caption styles that remain grounded in the same evidence. Unlike conventional captioning systems that often produce generic descriptions, CLARIS AI first constructs an evidence ledger from multiple perception modules and then performs a single multimodal reasoning step to generate all caption styles consistently. This design preserves factual consistency while allowing different writing styles—including formal, sarcastic, tech humor, and everyday humor—without changing the underlying facts.
13 Jul 2026