Generative-AI evaluation & RLHF.
High-signal human judgment to align and benchmark generative models: image and LLM.
evaluate · rank · align
What we do.
Every task runs through our expert-managed QA pipeline, with PII masked and a reason recorded on every item.
Aesthetic A/B evaluation
Side-by-side quality and preference judgments.
Prompt-fidelity matching
Does the output actually match the prompt?
Typography & anatomy QA
Text legibility and human-anatomy correctness.
Preference ranking / RLHF
Ranked preference data to align model behavior.
Red-team-style review
Adversarial and edge-case probing of outputs.
UI / screenshot annotation
Labeled interface data at scale.
Modalities & techniques
image evaluation
text
multimodal
preference ranking
Ran four parallel image-evaluation frameworks for Anthropic and annotated 50,000 UI screenshots across 50 apps with PII masking.
FAQ.
The questions clients ask us most about generative-ai evaluation & rlhf.
Calibration sets, regular re-tests and drift monitoring keep every evaluator aligned to your rubric.
Yes, we implement your rubric exactly, or help you sharpen it where criteria conflict.
Time-on-task floors, justification requirements and audits on “neither” / tie rates catch low-effort work.
Let's talk
Tell us what you're building.
Send us your data challenge and we'll scope a pilot, usually within a couple of working days.