A quick look at how Graveiens AI partners with teams to deliver human data for AI models.
Whether the data is ours or yours, we validate it against a written standard and give you the metrics to trust it — or the findings to fix it.
Even the best-collected data drifts, mislabels and duplicates over time. Graveiens AI provides independent data validation and review services that verify accuracy, consistency and completeness before your models ever see the data — reducing the silent errors that quietly cap model performance.
Our trained reviewers and subject-matter experts check labels against your guidelines and a gold-standard set, flag edge cases, and return measured quality scores you can act on. Validation runs as a standalone service or as the final gate on any annotation or collection project.
Talk to our data-QA teamFrom label accuracy to dataset-level consistency and bias checks.
Item-level verification against guidelines, with correction and rework of failed samples.
Cross-annotator consistency, duplicate detection and class-balance checks across the dataset.
Measured accuracy, precision and agreement scores against a trusted reference set.
Targeted review of rare classes and sensitive cases that skew model behaviour.
Representative programmes our validation services support.
An independent check on data delivered by other vendors or crowds.
A final accuracy gate before datasets enter training.
Finding the mislabelled data behind stubborn model errors.
Every validation project follows the same path: we align on your acceptance criteria, sample and score against a gold standard, correct and re-check failing items, then hand back clean data with a transparent quality report. Because you approve deliverables before invoicing, a first data validation pilot is close to zero-risk.
Start a validation pilotHow our data validation and QA services compare with other providers on coverage, accuracy and QA.
| Provider | Core focus | Modalities | QA / accuracy approach | Engagement model |
|---|---|---|---|---|
| Graveiens AIUs | Independent data validation and QA — schema checks, gold-set audits | Text, image, audio, video, multilingual | Four-stage QA vs a gold standard, ISO 9001:2017 | Pay-on-approval pilots, managed programs |
| Macgence | Dataset QA and annotation review | Text, image, audio, video | Managed crowd with human QA | Project-based managed teams |
| Cogito Tech | Data quality and review | Image, video, text | Human-in-the-loop QA | Managed teams |
| Shaip | Dataset QA and audits | Text, audio, image | Domain-expert QA | Off-the-shelf datasets plus services |
| iMerit | Data QA and review operations | Image, video, text | Expert-in-the-loop QA | Dedicated managed teams |
| Sama | Annotation QA and review | Image, video, text | SamaAssure QA | Managed workforce |
| Surge AI | Data quality and 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.
A second set of expert eyes on data quality — yours or a third party.
Gold-set metrics and agreement scores you can defend.
Domain experts for judgments automated checks cannot make.
Invoiced only for approved deliverables.
Send us a sample task. You only pay for deliverables you approve.
Book a pilot