Self-correcting evaluation
Automated loops that detect visual flaws, correct them, and re-evaluate outputs until they meet defined quality criteria.
Research
Our research teams build systems that evaluate, correct, and benchmark image and video AI models across real-world e-commerce use cases.
E-commerce benchmarks
Purpose-built benchmarks for fashion, product catalogues, moodboards, and other commerce workflows.
Taste systems
Research measuring visual taste, aesthetics, and brand fit in generated imagery.
Latest research
Publication · Oct 2, 2026Video, made for 1Video moves from something made once and sent to many, to something directed once and rendered for each person, often while they watch.Sai KrishnaRead the post →
Publication · Sep 7, 2026 · 28 min readBuilding a Self-Improving Visual Evaluation HarnessHow we built a closed-loop agent that can judge, repair, re-verify, and learn from failures in e-commerce image generationHrithwik BharadwajRead the post →