Human-in-the-loop AI evaluation at enterprise scale — domain experts in medicine, law, finance, and code, plus native speakers. Hired, trained, & managed by Shaip so you can ship models faster.
Building production-ready LLMs demands rigorous human evaluation. But creating that capability in-house is expensive, slow, and fragile — especially at scale or across multiple languages.
Credentialed professionals — doctors, lawyers, engineers — who can reliably evaluate AI outputs take months to source, not weeks.
Translating your scoring guidelines into reliable evaluator behaviour requires calibration tests, and rework before data quality stabilises.
Managing quality across 50+ distributed evaluators is a full-time QA function most AI teams cannot absorb. Without monitoring, agreement drifts and datasets become unusable.
Native speakers with domain expertise across Arabic, Japanese, Hindi, and 47 other languages cannot be economically sourced or managed without a global operational infrastructure.
Every understaffed evaluation sprint is a week competitors gain ground — and a dataset your model cannot safely learn from.
Shaip provides human-in-the-loop LLM evaluation through a fully managed workforce service. We own recruiting, training, QA, and delivery. You define the rubric — we deliver the results.
We source and vet evaluators matched precisely to your domain — medical, legal, financial, technical, or multilingual. Real credentials, verifiable expertise, no generic crowdworkers.
From hiring and onboarding to rubric training, calibration, continuous QA, and performance monitoring — Shaip owns the entire LLM evaluation workforce lifecycle from day one.
Deploy 5 evaluators for a focused pilot or 50 for a major model launch. Scale up for releases, down between sprints — no long-term headcount commitments, no staffing delays.
Vetting, project-specific training, inter-rater reliability checks, calibration rounds, and continuous audit sampling ensure every dataset meets the quality bar your model needs to ship safely.
Shaip manages every stage of the evaluation workforce lifecycle — you stay focused on model development, not staffing and QA logistics.
Tell us your domain, target languages, scoring framework, volume, and timeline. Don't have a rubric yet? Our evaluation specialists help you design one optimised for your model's use case.
We source domain-matched evaluators from our global network, run verification, and deliver project-specific training — including calibration rounds and inter-rater reliability alignment before data collection begins.
QA-monitored team delivers scored outputs, preference rankings, rationales, and error classifications in your exact format — ready for RLHF, SFT, safety, or benchmark pipelines.
From pre-training data quality to post-deployment safety monitoring — Shaip provides the right credentialed evaluator for every stage of your AI development lifecycle.
Experts compare model outputs and rank by quality, relevance, and usefulness — ideal for RLHF training data.
Domain specialists verify claims, check sources, and flag fabricated or incorrect information before it reaches production.
Trained reviewers identify harmful content, bias, offensive language, and policy violations before deployment.
Evaluators assess retrieval quality, source relevance, and whether citations actually support model claims.
Native speakers test your LLM across languages, catching translation errors, cultural missteps, and localization issues.
Medical, legal, financial, technical — real-world experts who understand compliance, accuracy requirements, & industry norms.
Shaip supports every established human evaluation framework — or we design a custom protocol tailored to your model’s specific quality, safety, and domain requirements.
Structured multi-criteria evaluation. Evaluators score each output on defined dimensions: correctness, completeness, tone, safety, groundedness, policy adherence, and brand alignment.
Evaluators choose the better response between two model outputs — the gold standard method for generating RLHF preference data and comparing competing model versions or prompt variants at scale.
Expert-verified reference outputs serve as ground truth for regression testing, benchmark anchoring, and calibrating automated evaluation pipelines — preventing quality regressions as models evolve.
Human expert panels validate and calibrate automated AI judges against human baselines — ensuring your auto-eval pipeline doesn't drift from the quality standard your users actually experience.
Native speaker evaluation covering regional dialect appropriateness, cultural context, idiomatic correctness, and localised quality — far beyond what BLEU scores or translation models can detect.
Have a proprietary schema, internal taxonomy, or existing rubric? We train evaluators to your exact specifications — output formats, quality bars, and delivery pipelines.
The difference is accountability. Shaip is a fully managed service — we own quality, consistency, and delivery. A marketplace gives you access to talent and leaves all management to you.
We recruit evaluators precisely matched to your vertical — not generic crowdworkers. Real expertise, not approximations.
Deploy 5 evaluators or 50. We move fast. Most projects reach production within one week of kickoff.
Hiring, onboarding, training, QA, performance monitoring — we handle it all. You define the rubric; we deliver the results.
Calibration rounds, inter-rater reliability checks, continuous audits, and performance monitoring built into every project.
SOC 2 Type II, HIPAA-compliant, and GDPR-ready. NDA-based engagements. Your data never leaves your control.
Scale up for major releases; scale down between sprints. No long-term headcount commitments, no staffing overhead.
Choose the path that fits your project size.
Get 5–50 expert evaluators running in days. No long-term commitment. Validate quality before scaling.
500+ evaluators, fully managed end-to-end. SOC 2, HIPAA, GDPR compliant. Dedicated project management.
Most projects can begin within a few days once requirements, domains, and languages are confirmed.
We need your evaluation goals, sample prompts/outputs, scoring rubric (or we can help define it), and expected volume.
Yes. We recommend starting with a pilot to calibrate scoring, validate quality, and refine guidelines before scaling.
Yes. We deliver structured preference rankings, scoring, and labeled outputs that support RLHF and model improvement workflows.
We use vetting, project-specific training, calibration rounds, audits, and continuous QA to ensure reliable results.
Yes. Evaluators can assess full chat flows, context retention, reasoning consistency, and response behavior over long conversations.
Yes. Native speakers evaluate fluency, tone, dialect accuracy, and cultural context—not just literal translation.
Yes. We provide real domain experts who understand terminology, compliance risks, and accuracy requirements in your industry.
You receive structured evaluation data such as scores, rankings, issue tags, rationales, and error classifications in your preferred format.
Yes. Shaip supports NDA-based engagements and compliance-aligned workflows (SOC 2, GDPR, HIPAA-ready) based on project needs.
