Annotation, handled end to end
Diverse annotators. Validated quality. Delivered on your timeline.
Building a model that works outside a narrow slice of users is a performance argument, not just a moral one. Sarvam AI proved it - its diverse-annotator approach outperformed a model four times its size on Indic language benchmarks, simply because the training data reflected the people using it. That's the same principle behind every batch we deliver. Most vendors ask you to choose between speed, cost, and quality. We built Managed Services so you don't have to.
From raw data to validated training data in four steps
- 01
Scope
Tell us your annotation guidelines, data type, and quality bar. We match you with annotators who fit the task and the market.
- 02
Annotate
Our diverse annotator network gets to work, drawing from the same demographics and markets your model needs to understand.
- 03
Validate
Every batch runs through our Intent Preservation Engine before it reaches you. We catch misunderstood intent, not just formatting errors.
- 04
Deliver
You get production-ready training data in 2 to 14 days, not the 6-to-21-day industry average.
Four things most annotation vendors cannot say
Speed without the tradeoff
2 to 14 day delivery against a 6 to 21 day industry average. Fast doesn't have to mean rushed when validation is built into the process instead of bolted on at the end.
Representative, not just available
Our annotators come from the Tier 2 and Tier 3 cities and markets your model needs to serve, not just wherever labor happens to be cheapest that quarter.
Validation on every batch, not a sample
Most vendors catch quality issues through spot checks after the fact. Our Intent Preservation Engine validates every batch before it reaches you, checking whether the annotator understood the task, not just whether they followed format.
Built to last, not just to scale
Human-validated annotation doesn't degrade the way model-refined data does across repeated generations. What you get today holds up as your model keeps training on it.
What actually happens to your data
Your raw data enters the pipeline - text, image, audio, or video - with your guidelines and quality bar attached.
Work is matched to annotators fit for the task and the market, drawn from the Tier 2 and Tier 3 cities your model needs to understand.
Every completed batch is scored for meaning, not just formatting - catching misunderstood intent before it ever reaches you.
Validated batches land in a live metrics view: what passed, what got flagged, and why. Nothing is a black box.
Your data exports in the format your training pipeline already expects. Nothing reaches you without a quality score attached.
Nothing skips validation. Nothing reaches you without a quality score attached.
Where your data actually goes
Your data stays encrypted at rest, and every annotator works under NDA. If you use IPE as part of your engagement, validation happens in-process on your data, and nothing gets stored on our side beyond what you need for delivery. A SOC 2 audit is currently in progress - we'd rather tell you exactly where we stand than stay quiet about it.
Our first structured pilot
Before taking this to market, we ran a structured pilot end to end: 105 annotations across 7 distinct task types, completed by 14 annotators across 5 Indian states, validated through the Intent Preservation Engine at approximately 93% intent preservation. This was not a simulation - same process, same validation layer, same annotator network we run today, at an earlier stage. We're sharing real numbers rather than dressing this up: a smaller number you can trust is worth more than a big one you can't verify. We're actively working toward 300+ annotators by the end of the year.
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Pricing built around your project, not a plan tier
Managed Services pricing depends on annotation volume, task complexity, and data type, so we don't publish flat per-seat tiers. Most engagements are priced per annotation or hourly depending on the work involved. Tell us what you're building and we'll put together a quote that reflects the scope of your project. Not ready for a full engagement? We can start with a smaller pilot batch so you can see real output before scaling up.
Common questions
How is Managed Services priced?
Per annotation or hourly, depending on volume, complexity, and data type. Book a demo and we'll walk you through a quote scoped to your project.
How fast can you deliver?
2 to 14 days depending on volume and complexity, against an industry average of 6 to 21 days.
How do you ensure annotator quality across different markets?
Our annotators are sourced directly from the regions and demographics your model is meant to serve, then every batch is validated through our Intent Preservation Engine before delivery.
Do you work with data types beyond text?
Yes - our network covers image, audio, and text annotation, with video annotation available depending on project scope.
What happens if a batch does not pass validation?
It gets flagged, corrected, and revalidated before it ever reaches you. You only receive data that has cleared the Intent Preservation Engine.
Comparing us to Scale AI, Appen, or Surge?
Most vendors sell you on scale or price. Neither matters if the model still fails once it meets real users in real markets. If you're comparing vendors, ask one question: how do they verify quality beyond a spot check? That question is exactly what our Intent Preservation Engine was built to answer.