Organic data for the age of AI

Your data, shaped by human thought

AI learns from data. We make sure that data carries real human knowledge — not synthetic noise. People who read, reason, and decide. That's what goes into every label.

Scroll
Our Belief

The best models learn from people, not just about them

We built a process where people contribute what matters most — their judgement. Every label in our pipeline exists because someone understood the data, not because a system automated a guess. It's a different kind of work, and it produces a different kind of result.

How We Work

Three stages. Each one asks a person to think.

01

Intake & Context

理解 — Understanding

Before any label is applied, contributors study the domain. They learn the context, the edge cases, the intent behind your data. This isn't a task — it's the beginning of understanding.

02

Human Annotation

判断 — Judgement

Multiple people work through the same data independently. We compare their answers, measure agreement, and use known benchmarks to surface who's getting it right. Consensus builds quality.

03

Review & Delivery

検証 — Verification

Answers are cross-checked against known truths and peer responses. Edge cases get resolved through evidence, not shortcuts. What reaches your model has been tested, not just completed.

99.2%
Label Accuracy
Across Projects
0%
Synthetic or
Auto-Generated Labels
3x
Review Passes
Per Data Point
100%
Human Annotated
& Verified
Good data comes from real understanding. We make sure it gets there.

Industry Standard

Crowd-sourced annotation
Distributed to thousands of anonymous workers optimizing for speed, not understanding.
Auto-label with human spot-check
Machine generates labels, humans review a sample. Errors propagate silently.
Volume-first pricing
Optimized for throughput. Quality is a metric to be gamed, not a standard to be met.
Black-box delivery
You receive labels. No reasoning, no audit trail, no insight into how decisions were made.

General Data

People who think, not just click
Individual contributors who learn your domain and apply real judgement to every data point.
Knowledge in, not just labor
Every data point is processed by someone contributing their reasoning. Not clicks. Not keystrokes. Thought.
Quality-first engagement
We scope for accuracy and depth. You pay for data you can actually train on, not volume you have to filter.
Reasoning trails included
Every annotation comes with the thinking behind it. You see not just the answer, but how a person got there.

Start with data that knows something

Tell us about your dataset. We'll show you what human knowledge looks like inside it.

Get in Touch

Typically respond within 24 hours