Real-world agentic AI evaluation
Human JudgmentFor Agentic AI.
Validate autonomous agent performance, alignment, and safety with expert human evaluation, adversarial testing, and rubric-driven scoring at scale.
One platform. Three evaluation engines.
Evaluator Network
- Task completion judges
- Preference raters
- Red team testers
- Output reviewers
- Domain evaluators
Expert Network
- AI safety researchers
- Alignment specialists
- Domain SMEs
- Policy experts
- Technical red teamers
Evaluation Layer
- Rubric calibration
- Inter-rater reliability
- Failure mode taxonomy
- Policy gap analysis
- Adversarial coverage
Build for the real world
Task Completion
Multi-step tasks, Tool use, Success rate
Safety Evaluation
Harmful output, Refusal quality, Edge cases
Red Teaming
Adversarial prompts, Jailbreak attempts, Policy violations
RLHF & Preferences
Pairwise ranking, Likert scoring, Preference data
Reasoning & Planning
Chain of thought, Multi-hop, Long-horizon tasks
Tool Use & Agents
API calls, Code execution, Browser agents
The Harbor Data Flywheel
From agent output to validated, production-ready AI.
A continuous loop that turns expert human evaluation into safer, better-aligned agentic systems.
Learn moreEvaluation Types
Human Preference Data
Pairwise and scalar preference labels from expert and crowd evaluators for RLHF, DPO, and reward model training.
- Pairwise comparison judgments
- Scalar quality ratings
- Multi-criteria scoring rubrics
- Calibrated inter-rater agreement
Why teams choose Harbor
Evaluation at Scale
Deploy structured evaluation programs in days — with calibrated evaluators and rubrics ready to go.
Expert-Level Judgment
Domain specialists and AI safety researchers evaluate outputs that require genuine expertise, not just language fluency.
Defensible Quality
Multi-stage review with inter-rater reliability metrics ensures evaluation data your alignment team can trust.
Example Agentic Programs
RLHF Preference Dataset
Red Team & Safety Dataset
Agentic Task Benchmark
Better Agents Start With Better Evaluation.
Expert evaluators. Structured rubrics. Agentic AI datasets at scale.