Field-sourced data · 60+ countries · Live collection network

The real-world data layer
for AI that ships.

Ayta sources, labels, and validates image, video, audio, and text data at scale — built for teams who need ground-truth, not guesswork.

What the network delivers
40+
languages & locales covered
98.4%
average QA pass rate
10K+
vetted field collectors
72hr
typical pilot turnaround
Services

One pipeline, every modality.

From a single pilot batch to a standing collection program — we run the recruitment, capture, and QA infrastructure so your model team never has to.

Vision Datasets

Selfies, environments, products, documents, and gesture capture — shot to spec, across the demographics and devices your model actually needs.

Image · Video · Depth

Speech & Audio

Read speech, spontaneous conversation, accent and dialect sets, environmental sound — recorded clean or in the wild, on purpose.

Speech · Ambient · Multi-accent

Text & NLP

Handwriting samples, transcription, structured surveys, and annotation work — with linguist-reviewed quality at every batch.

Annotation · OCR · Surveys

Multimodal & Localization

Paired image-audio-text sets and region-specific localization projects, built for teams training across markets and languages at once.

Cross-modal · Regional

Specialized Capture

Healthcare-adjacent, automotive, and AR/VR datasets that need protocol-level rigor and informed-consent handling built in.

Consent-verified · Compliant

Managed QA & Delivery

Four-layer review, metadata validation, and clean handoff — raw assets, QA reports, and consent records, packaged the way your pipeline expects.

Audit · Metadata · Packaging
How it runs

From brief to delivered dataset.

Every engagement runs the same disciplined sequence — small enough to move fast, structured enough to hold up under your model's QA bar.

01

Scope

Geography, demographics, volume, timeline, and budget locked before a single asset is collected.

02

Pilot

A small test batch validates instructions, speed, and quality before we scale spend or headcount.

03

Collect

Field network and recruitment channels activate against the approved pilot parameters.

04

Review

Four-layer QA — completeness, technical, guideline match, and random audit — on every batch.

05

Deliver

Packaged assets, metadata, QA reports, and consent records, handed off on your schedule.

Data types

Built for what your model is missing.

Images Selfies, environments, products, documents — at the angles and lighting your model never sees in stock data.
Video Activity recordings, gesture sets, device interaction footage, scenario-based capture.
Audio Read and conversational speech, accent diversity, environmental sound, recorded on real devices.
Text Handwriting, transcription, annotation, and structured survey response data.
Multimodal Paired sets across image, audio, and text for models that need to reason across senses.
SPECSTATUS
IMAGE_FEED Vision capture
v2.4ACTIVE
Quality

Trust is the product.

Datasets that fail review cost more than the ones that pass slowly. Every batch clears four independent checks before it reaches you.

Layer 01

Completeness

Every required field, file, and consent record is present before anything moves forward.

Layer 02

Technical validation

Resolution, format, duration, and signal quality checked against your spec automatically.

Layer 03

Guideline match

Human reviewers confirm each asset matches your project's exact collection brief.

Layer 04

Random audit

An independent sample is re-checked before delivery to catch what slips through.

Your model is only as good
as the data behind it.

Let's scope a pilot this week.

Start a project →