Define the work
Set the question, source material, intended data use, and an explicit evaluation rubric.
DOMAIN EXPERTISE. TRAINING-READY DATA.
Better AI begins
with expert judgment.
Turn the work your experts know best into data your models can learn from. Capture answers, preserve evidence, and review every record before it leaves your team.
THE ANATOMY OF A GOOD RECORDILLUSTRATIVE EXAMPLE / FINANCE
01 / REAL-WORLD TASKRevenue grew.
Revenue grew.
Did performance improve?
A fictional distributor reports 20% revenue growth, while gross margin falls from 30% to 23%.
Financial analysisEvidence required
02 / EXPERT CONTRIBUTION
“Growth alone is not enough. Gross profit fell from 30 to 27.6 on a revenue index of 100 → 120. Investigate pricing, product mix, and input costs before attributing the change.”
✓
03 / INDEPENDENT REVIEWCorrectness · Evidence · Completeness
Quality gateTHE METHODFrom domain knowledge
From domain knowledge
to dependable datasets.
Start with a real task. Define what a good answer looks like. Keep the expertise and the evidence together.
Capture expertise
Experts contribute an answer and supporting evidence in a structured workspace.
Review independently
A separate reviewer checks quality against the rubric and records a decision.
Deliver with context
Export approved records as JSONL, with provenance and review metadata preserved.
BUILT AROUND THE WORKFor knowledge that
For knowledge that
doesn’t fit a checkbox.
Our first workflows focus on finance and business operations. Use synthetic examples to explore the pilot before introducing authorized enterprise data.
FINANCE ↗
Make the numbers
explain themselves.
Build examples for variance analysis, financial interpretation, and evidence-backed business questions.
BUSINESS OPERATIONS ↗
Capture the judgment
behind the process.
Document exception handling, supplier decisions, and operational tradeoffs against your team’s rubric.
UNIFYDATA / INITIAL PILOTA focused workspace.
A focused workspace.
A complete data workflow.
Task creation, expert contributions, independent review, and approved JSONL export are the scope of this release. Built on Label Studio Community Edition.
Private, single-team pilot. Expert recruiting, automated model evaluation, fine-tuning, billing, and enterprise SSO are not included.