A quick look at how Graveiens AI partners with teams to deliver human data for AI models.
Leaderboard scores rarely tell you if a model is safe to ship. Our trained human raters and STEM/domain SMEs assess your outputs, scoring reasoning, factuality, safety and helpfulness against a rubric you define. Pair scoring with our LLM fine-tuning and data validation to close the loop from measurement to improvement.
Start an evaluation pilotBuilt as a repeatable LLM evaluation framework, we score model outputs against your rubric across quality, safety, reasoning and factuality — and surface the failure modes that decide whether a model is ready to ship.
Automated metrics only go so far — real quality needs human judgement. Graveiens AI provides expert LLM evaluation: rubric-based scoring, side-by-side comparisons, factuality and safety checks, and red-teaming, delivered by calibrated raters and subject-matter experts across 25+ languages.
We design scoring to your criteria, calibrate against gold standards, and return measured, defensible scores through a four-stage quality workflow — so you can trust the numbers behind a release decision.
Talk to our evaluation teamFrom rubric scoring to safety and factuality.
Detailed, criteria-based scoring for accuracy, tone and helpfulness.
Pairwise preference judgements between models or versions.
Fact-checking and citation review for reliable outputs.
Adversarial testing and safety scoring for robust models.
Representative programmes we support.
Human scores to gate model releases with confidence.
Expert grading for medical, legal and STEM outputs.
Evaluation across 25+ languages and locales.
Evaluation is only useful if it is consistent and credible. We calibrate raters against gold standards, bring real domain expertise, and document methodology so results hold up to scrutiny. Pay-on-approval keeps a first evaluation pilot low-risk.
Start an evaluation pilotHow our LLM evaluation and red-teaming services compare with other providers on focus, expertise and QA.
| Provider | Core focus | Modalities | QA / accuracy approach | Engagement model |
|---|---|---|---|---|
| Graveiens AIUs | Human and rubric-based LLM evaluation, safety and red-teaming | Text, dialogue, code, domain prompts | Domain-expert graders vs a rubric, ISO 9001:2017 | Pay-on-approval pilots, managed programs |
| Macgence | Model evaluation and RLHF data | Text, dialogue, prompts | Managed crowd with human QA | Project-based managed teams |
| Cogito Tech | LLM output scoring and annotation | Text, dialogue | Human-in-the-loop QA | Managed teams |
| Shaip | Domain model testing and validation | Text, audio, domain prompts | Domain-expert QA | Off-the-shelf datasets plus services |
| iMerit | Model evaluation and data operations | Text, dialogue, multimodal | Expert-in-the-loop QA | Dedicated managed teams |
| Sama | Generative AI scoring and alignment | Text, image, multimodal | SamaAssure QA | Managed workforce |
| Surge AI | RLHF and model rating for LLMs | Text, dialogue | Expert human raters | API plus managed service |
Compliance-first delivery and a pay-on-approval model that de-risks every engagement.
STEM and domain SMEs who can judge correctness, not just fluency.
Inter-rater agreement tracking keeps scoring consistent and defensible.
Native-speaker evaluation across 25+ languages.
Invoiced only for approved deliverables.
Send us a sample task. You only pay for deliverables you approve.
Book a pilot