Why AI buyers need real-world evaluation data
AI developers need real business data not only to train models but to evaluate them — testing whether a model can actually do support, sales or finance work.
Training is only half the need
Public discussion of AI data focuses on training. But developers also need evaluation data: real tasks with real outcomes, to test whether a model can actually resolve a support ticket, qualify a lead or reconcile accounts.
Why it must be real
- Synthetic test cases miss the messiness of actual work.
- Public benchmarks are gamed and exhausted quickly.
- Real operational records — anonymized — show whether a model performs on tasks businesses care about.
This evaluation demand is documented in industry reporting on AI data spending (Reuters).
What this means for partners
Companies with 50+ full-time employees at peak hold exactly the task-and-outcome records buyers evaluate against. Introduce one to SourceX; if a deal closes and SourceX collects its fee, you can earn 25% of that fee, up to $100,000 per company.
- Step 1Share your linkSend your personal link to a company you know.
- Step 2Company appliesThe company applies itself at /apply.
- Step 3Buyer selects and paysThe buyer selects and pays for the data and SourceX receives its fee.
- Step 4You get your rewardYour share of SourceX fees becomes payable.
Free resources
- Cash flow calculator — A 12-month cash forecast with shortfalls highlighted.
- Referral earnings calculator — Hypothetical partner earnings with the per-company cap.
- Cash conversion cycle calculator — DIO, DSO, DPO and the cash conversion cycle.
- All free tools · MCP resource center
By SourceX Partnerships Team · Published 2026-10-09 · Updated 2026-10-08
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