What we make
GATA is a parallel production workspace. You bring a script or a brief; the workspace keeps cast, look, and continuity locked while you iterate on shots, scenes, and language versions. The same character can appear in the UK launch film, the German cutdown, and the gaming-trailer remix — without re-prompting from scratch each time. See character consistency, parallel production, and localised versioning for the working definitions.
Why we built it
The current generation of AI video models (Veo, Sora, Kling, Seedance, Pika) is genuinely useful at the shot level and genuinely unusable at the campaign level. A marketing team that needs ten shots, three languages, and a recognisable hero has to either accept characters that drift between cuts, or rebuild the project from scratch for every variant. GATA is the layer that makes those models production-ready: a workspace that holds context across shots, scenes, and language versions, and lets a team review and approve work the way they already do.
We are deliberately not an AI dubbing or lip-sync tool. Localisation in GATA means re-casting voices, re-writing copy, and re-generating scenes per region — visual versioning, not audio replacement. If the right answer is to dub an existing video, HeyGen, Rask, and ElevenLabs do that job well.
Founder
GATA is built by Cinar Baymul, an AI engineer who has spent the last few years on the unglamorous part of generative AI: making models reliable enough to ship. At DraftWise (Y Combinator) he built production LLM, RAG, and agentic features for lawyers, including the contract checker that became the company's largest revenue product. He founded WhiteCoat AI before that, and ran data science at a mobile-games studio before that — so GATA comes out of the same place its customers live: production AI, plus the marketing and content economics of getting video out the door.
Today's video models are brilliant in a demo and brittle in a campaign. He started GATA to build the layer in between — the workflow that holds cast, look, and continuity together across a real production — which is the kind of reliability problem he's solved before. He has a DPhil from Oxford and a decade in data and machine learning, and is GATA's product owner, lead engineer, and the person who answers your email.
Reach him at cinar@gata.ai, or find him on LinkedIn and GitHub. Follow GATA on X and YouTube.
Who we build for
Four audiences shape the roadmap: marketing producers at startups and scale-ups, creative directors at agencies, game-studio marketing leads working on trailers and cinematics, and localisation managers at content publishers. If you do any of these jobs and you have ten minutes, we would like to hear what is in your way — email cinar@gata.ai.
How we work
Small team, narrow focus, no investors driving an unrealistic roadmap. We ship weekly, talk to customers more often than to analysts, and treat the production workflow — not the model — as the product.
GATA AI is a trading name of Exchester Ltd, registered in England and Wales (company number 12601661). Legal, privacy, and procurement documents live at /privacy, /terms-of-service, /dpa, and /subprocessors.