Built by people who've shipped the data pipeline before.
We started as a small collection unit running pilots for computer vision teams who couldn't find the demographics, locations, or edge cases they needed anywhere else.
Why Ayta exists.
Most AI teams lose more time sourcing and validating data than building the model itself. Off-the-shelf datasets cover the easy cases; the gaps — specific demographics, regions, accents, lighting, devices — are exactly what's hardest to find, and exactly what determines whether a model holds up outside a benchmark.
Ayta runs a global field network of vetted collectors and regional coordinators, paired with a multi-layer QA system built specifically for AI training data — not repurposed survey tooling or crowdsourcing left unsupervised. We work in image, video, audio, text, and multimodal collection, with dedicated programs for localization and underrepresented-language data.
We're a small, senior team by design. No account-manager layers, no 200-page SOWs — just a direct line to the people running your collection program, and a QA bar we hold ourselves to before you ever have to ask.
Mission & vision.
Our Mission
Give AI teams the real-world data they can't source anywhere else — collected, annotated, and validated by a team that treats quality as a process, not a promise.
Our Vision
A world where no AI model fails in production because the training data never reflected the real world it has to operate in.
What makes us different.
Quality over speed
A fast dataset that fails your QA bar costs more than a slower one that passes. We pilot first, every time, before scaling a single collection program.
Consent is not optional
Every participant is informed, every record is documented. Specialized and regulated-adjacent projects get protocol-level rigor from day one.
Direct, not layered
You talk to the people running your program. No relationship managers relaying messages between you and the work.
From pilot batches to a standing network.
Pilot collection work
Started running small, focused image and audio collection batches for computer vision teams who couldn't source specific demographics anywhere else.
Built the field network
Formalized recruitment channels and regional coordination — city-level collectors, demographic specialists, and a QA team independent of the collection side.
Multimodal & localization
Expanded into paired multimodal sets and dedicated localization programs, with regional QA teams covering underrepresented languages.
Standing collection infrastructure
Running ongoing programs alongside one-off pilots, with the same four-layer QA system applied across every modality we collect.
Built to be efficient, not expensive.
A lean, senior team keeps overhead down and decisions fast — so more of your budget goes to actual collection and QA, not layers of management.
Lower overhead, lower cost
No relationship-manager layers or bloated account teams — a smaller team means more of your budget funds the work itself.
Faster time to pilot
Fewer approvals and a senior-only team mean your pilot moves from scope to delivered data in days, not weeks.
Cost that scales predictably
The same team that runs your pilot scales your program, so cost stays predictable as volume grows instead of climbing with headcount.
Want to see how we'd
run your pilot?
Tell us what you're building. We'll tell you exactly how we'd collect for it.
Get in touch →