Projects
Redrob product and research.
Redrob$6.8M ARR (Nov 2025) · 10M+ signups · 500 universitiesTechnical co-founder and CTO since March 2018. The platform reached $6.8M ARR and 3 million users across 500 universities in India as of the Nov 2025 Series A, and later 10M+ user signups, built by an engineering organization spread across Seoul, India, and the US.
Redrob EvalPublic harness, Apache-2.0LLM eval workbench: Compare, Evolve, Deploy. Blind brackets become routing labels. Test spent once. Relative cost only. Apache-2.0, clone and run.
Redrob ConsoleRouted Indic text APIClient-facing API dashboard for a routed Indic text stack: Sarvam’s open model and other open backends behind one Redrob completion surface. I owned onboarding, integration support, and per-customer cost tuning.
Redrob ImageBlind A/B vs GPT Image 2: large gap ruled out, parity not shownOpen-weight Z-Image Turbo (Apache-2.0, commercial OK). ~8 steps, plain Diffusers. Blind vs GPT Image 2: 44-16-30 (n=90). ~1.8s/image. Photo/portrait, weak on text.
Redrob Tune60s track in 14-23s, self-hostedMusic on ACE-Step 1.5 through ComfyUI: Tune Fast and Tune Pro. A 60-second track landed in about 14s on Fast and about 23s on Pro in the Jul 28 preference bake-off. Tune has no standalone release; it ships as the Music tool inside Redrob Studio. Samples below include winners from that run and earlier bake-offs.
Redrob StudioSafety gate: 100% recall on a 6,000-prompt evalLocal Next.js studio for image and audio tools on your own ComfyUI GPU, with dual LLM/VLM safety gates. On a 6,000-prompt NSFW/SFW eval across image, text, and audio: 99.92% accuracy, 100% recall, five false positives. No chat surface and no video generation stack; home is a tools catalog and bake-offs sit in the same shell. Latency and preference claims live on Image and Tune.