Human intelligence for better models
GroundTruth AI pairs expert reviewers with rigorous quality systems to deliver data labeling, human evaluations, model evaluations, and red teaming—so your team ships safer, more capable AI.
Services
Every kind of human data your models need
One partner for the full spectrum of human-in-the-loop work, backed by vetted experts and rigorous quality controls.
Data labeling
High-quality annotation across text, image, audio, and video—from bounding boxes to complex taxonomies.
Human evaluations
Expert reviewers score model outputs against custom rubrics to measure quality, helpfulness, and safety.
Model evaluations
Structured benchmarking of model outputs to measure accuracy, capability, and regressions across releases.
Red teaming
Adversarial testing by trained specialists to surface failure modes, jailbreaks, and safety risks.
Quality audits
Independent review and gold-standard audits to verify accuracy and catch errors before delivery.
Robotics & physical AI
Reviewing and rating real-world clips, actions, and sensor data to train and validate embodied systems.
AI agents
Reviewing multi-step agent trajectories and tool use to evaluate reasoning, reliability, and task success.
Custom projects
Have a different project in mind? We build tailored workflows for any data type, domain, or set of requirements.
How it works
A quality-first workflow, end to end
Scope & onboard
We align on your taxonomy, rubrics, and edge cases, then assemble a vetted team matched to your domain.
Label & evaluate
Annotators work in a guided interface with built-in checks, while reviewers score and reach consensus.
Audit & deliver
Gold-standard audits and inter-annotator agreement gate every batch before it reaches your pipeline.
Iterate & scale
Continuous feedback loops refine guidelines and let you scale from pilot to millions of tasks.
Quality
Quality you can measure and trust
Accuracy is engineered into every step. We combine expert reviewers with layered quality systems so you can rely on every label and score.
- Multi-reviewer consensus on every evaluation task
- Gold-standard audits and inter-annotator agreement tracking
- Vetted, full-time experts — never anonymous crowdsourced labor
99.2%
Average label accuracy
98%
Inter-annotator agreement
3x
Reviewer consensus per task
<24h
Median pilot turnaround
Ready to give your models the human edge?
Start a pilot in days. Tell us about your data and we'll design a labeling and evaluation program tailored to your goals.