AI training data infrastructure · Vietnam
Your model is only as good asthe data it learns from.
Most suppliers only process the data you already have. TucTak also goes and gets what does not exist yet: a contributor network across Vietnam photographs, films and records exactly what you specify — then annotates it on the same platform.
Images · Video · Audio · Text — captured on site, annotated with verification
Annotation types
Bounding box · Classification · Segmentation · Keypoints · Vehicle damage
Delivery models
Self-service · Crowdsourced · Fully managed — same batch, up to 7× apart on unit price
Quality control layers
AI pre-check · Fraud prevention · Peer verification · Gold standard
Minimum commitment
Pay per image from prepaid credit — no framework contract, no volume promise
Services
Four ways we produce the data you need
From processing what you have, to capturing what does not exist yet, to a production AI model for motor insurance. The four compose — many engagements start as collection and move straight into annotation.
- 01
Data annotation
You have the data — we turn it into a training set
Our team in Vietnam annotates your images and video against your own label taxonomy, with an AI pre-labeling pass that cuts turnaround substantially. People verify and correct rather than draw from scratch.
- 02
On-the-ground collection
Data you cannot buy anywhere — we go and capture it
Tasks are dispatched to contributors in the exact provinces and venue types you need surveyed. Every submission is constrained by GPS coordinates, automated content checking and content hashing before it is ever paid for.
- 03
Vehicle damage assessment
A metered API for the insurance industry
Send scene photos, receive damaged parts, severity, confidence and a repair estimate. First-pass assessment becomes automatic, leaving adjusters to handle only the hard cases.
- 04
Ready datasets
Available today, not after a collection cycle
Already collected and annotated, available to license immediately. Inspect watermarked samples before you commit, then download through the dashboard or the API.
Why TucTak
Annotation vendors cannot go get it. Collection vendors cannot label it.
When you need a dataset that has never existed — shelf imagery from traditional markets, street signage, handwritten receipts from a specific region — you end up stitching two vendors together. And nobody signs for the gap between them: if the imagery is not good enough to annotate, whose problem is it?
What brings you here?
Three ways into TucTak
The platform serves three different groups. Pick the door that takes you straight where you need to go.
What dataset do you need?
Most customers start with a few hundred images to judge the quality themselves before committing volume. Nobody has to approve you first, and there is no minimum.