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Human evaluation of LLMs and AI agents by vetted domain experts. Shaip designs the rubric, runs the evaluation, owns quality, and delivers pipeline-ready results — no staffing, no marketplaces, no managing evaluators yourself.
LLM evaluation, or AI model evaluation, is the measurement of a model’s outputs against defined quality criteria. Expert-led evaluation is the practice of having qualified subject-matter experts — rather than crowd workers or automated metrics alone — judge the outputs of a large language model or AI agent against those criteria. Physicians score clinical answers, lawyers score legal reasoning, native speakers score fluency, and engineers score code.
Shaip runs this as a managed service: we translate your quality bar into a calibrated rubric, assign the right experts from a pool of more than 10,000, audit agreement and consistency throughout, and return scores, rankings, rationales and error taxonomies in the format your training or release pipeline expects.
Why teams outsource evaluation to Shaip
Standing up a qualified evaluation bench yourself is slow, and expert marketplaces hand you people, not results. Here is what that costs you — and how a managed project removes it.
How it works
A managed, end-to-end model evaluation workflow from brief to pipeline-ready delivery — with quality built in at every step.
We take your success criteria, failure modes and sample outputs and turn them into a scoring rubric with worked examples.
3–5 daysExperts are matched by credential, domain and language, then complete a calibration set. Only evaluators above the agreement threshold enter production.
Credential-verifiedBlind double-scoring on a sample, gold items seeded throughout, weekly agreement and drift reports.
Target 98% IRRScores, rankings, rationales, error taxonomies and corrected responses as JSONL, CSV or via API — with a findings summary and recommended fixes.
JSONL · CSV · APIWhat we evaluate
A repeatable LLM and AI model evaluation framework that scores your outputs across every dimension that decides whether a model is ready to ship — from single-response quality to full AI agent trajectories.
How we evaluate
We choose the human evaluation protocol that fits your decision — a release gate, a model-vs-model comparison, or a research question.
Absolute quality measurement against defined criteria — the backbone of release gates and regression tracking.
Choosing between model versions, prompts or vendors; produces preference data usable for RLHF and DPO.
Repeatable LLM benchmarks where experts write the reference answer first and outputs are scored against it.
Validating automated evaluators against human judgment before you trust them at scale.
Native-speaker scoring of language quality, dialect and cultural appropriateness in 50+ languages.
Long-context review, interactive probing or any bespoke evaluation protocol your research team specifies.
Why domain experts matter
Crowd workers can tell you if an answer reads well. Only a qualified expert can tell you if it is right — which is what human evaluation of LLMs is for.
Physicians, nurses and pharmacists score clinical accuracy, safety and guideline adherence.
Lawyers and paralegals evaluate legal reasoning, jurisdiction accuracy and risk.
Analysts and accountants judge numerical correctness and regulatory language.
Linguists in 50+ languages score fluency, dialect and cultural fit.
Developers assess code correctness, security and style across languages.
Experienced support and CX leads score chatbots, copilots and voice agents for accuracy, tone, escalation and task completion.
Create, curate, and collect custom-built datasets (text, speech, image, video) from across the globe based on custom guidelines.
Leverage 10,000+In-house global workforce and 500K+ Crowd-scale credentialed contributors. Real-time workforce capacity and efficiency.
Our proprietary platform & skilled workforce use multiple quality control methods to meet or exceed quality standards.
Our process streamlines, the collection process through easier task distribution, & data capture directly from the app & web.
Maintain complete data confidentiality by making privacy our priority. We ensure data formats are policy controlled and preserved.
Every collected dataset can be annotated, labeled, transcribed, and validated in the same workflow, delivering model-ready training data.
Get a calibrated rubric and a physician-, lawyer- or native-speaker-scored pilot back fast. Managed end to end, delivered in the format your pipeline expects.
Contact UsIt is the scoring of LLM or AI agent outputs by qualified subject-matter experts against a defined rubric, run as a managed project by Shaip rather than by a crowd or an automated metric alone. Shaip designs the rubric, runs the evaluation, audits quality and delivers pipeline-ready results.
We translate your quality bar into a calibrated rubric and score outputs with credentialed experts, screening at scale with automated metrics and reserving expert judgment for what automation cannot measure. You receive scores, rationales, error taxonomies and recommended fixes.
No. Shaip runs the evaluation end to end with its own experts and delivers the results. That keeps calibration, quality and accountability with us, not with your team.
A calibrated rubric and a qualified expert bench are typically in production within 10 days of the brief. Rubric design alone usually takes 3–5 days.
Credential verification, domain and language testing, a calibration set before production, blind double-scoring, seeded gold items and weekly agreement reports. We target 98% inter-rater agreement.
More than 20 professional domains including healthcare, legal, finance and software, and 50+ languages including 13 Indian languages.
JSONL, CSV or direct integration into your platform via API, with scores, rankings, rationales, error taxonomies and corrected responses, plus a summary of findings and recommended fixes.
Yes. Shaip evaluates single-turn answers, multi-turn conversations and full AI agent trajectories, including tool use and task completion, against a rubric we build with you.
Yes. Automated metrics provide coverage at scale; our experts handle the judgment calls and calibrate the automated judges so you can trust the scores at volume.
Pricing is per project or per evaluated item, scoped to your brief — there is no per-expert-hour billing. Shaip is SOC 2 Type II, HIPAA and GDPR compliant, and every engagement runs under NDA in access-controlled environments.
