How do you ensure evaluator consistency for RLHF?

HumanlyAI uses evaluator training and certification, gold datasets, calibration rounds, and QA review to maintain agreement and consistency over time.

Do you provide gold datasets for RLHF?

Yes. HumanlyAI can create gold tasks and ground-truth benchmarks, then use them to measure agreement, detect drift, and calibrate evaluators.

How fast can you run an RLHF pilot?

Pilot timelines depend on volume and QA depth, but many pilots can be completed within 7–14 days once scope and rubrics are finalized.

Certified human feedback for LLMs

RLHF Services for Reliable, Aligned AI

Q: What RLHF services does HumanlyAI provide?

HumanlyAI provides certified human feedback for RLHF, including pairwise preference ranking, rubric-based scoring, rationale capture, and structured outputs suitable for model training and evaluation.

Q: What do clients need to supply to start an RLHF project?

Typically clients supply prompts and model outputs (or candidate responses), evaluation goals, and any constraints or policies. HumanlyAI provides rubrics, trained evaluators, QA, and structured results.

HumanlyAI provides trained and certified evaluators for RLHF preference data, rubric-based scoring, and gold dataset calibration — so your model improves reliably, not randomly. If you’re new to this space, we recommend reading why most teams get RLHF wrong and what effective human feedback actually requires.

Pairwise Preference Ranking Rubric-Based Scoring Gold Datasets QA & Calibration

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Typical pilot turnaround: 7–14 days (scope dependent).

What we deliver

Preference Data

Pairwise comparisons and preference ranking with consistent guidance.

Two-response (A/B) preference ranking
Optional rationale capture
Task-specific rubrics

Quality Scoring

Structured scoring to identify regressions and improvement opportunities.

Factual accuracy scoring
Tone & professionalism
Overall quality scoring

Gold Datasets

Ground truth tasks to calibrate evaluators and measure agreement.

Gold task creation
Agreement thresholds
Drift detection & recalibration

QA & Governance

Quality gates to protect your signal.

Reviewer audits and spot checks
Rubric updates over time
Structured output delivery (CSV/JSON)

How it works

End-to-end RLHF workflow

1) Scope & inputs

You share prompts, candidate outputs, policies, and success criteria.

2) Rubrics & calibration

We define rubrics and run calibration rounds to align evaluators.

3) Evaluation + QA

Evaluators score and compare outputs; QA reviews agreement and issues.

4) Delivery

We deliver structured results for training loops, reporting, and regression checks.

Why HumanlyAI

Trained, certified evaluators — not crowd work

Certification gate

Training + quiz + gold dataset agreement before client work.

Consistency over speed

We optimize for reliable signal and safety, not fast clicking.

Built for iteration

Ongoing pods for continuous evaluation as your model evolves.

RLHF failures often stem from untrained evaluators and inconsistent judgment. We outline these common pitfalls in our post on why RLHF breaks down in practice.

FAQ

Common questions about RLHF services

What RLHF services does HumanlyAI provide?

Preference ranking, rubric-based scoring, rationales (optional), gold datasets, and QA calibration with structured outputs.

How do you ensure evaluator consistency?

Evaluator certification, gold datasets, calibration rounds, reviewer audits, and agreement monitoring.

What do we need to supply?

Prompts and outputs (or candidates), evaluation goals, and any constraints or policies. We provide the workflow, rubrics, and results.

How fast can a pilot run?

Many pilots can complete in 7–14 days after scope and rubric alignment (volume dependent).

Contact

Request an RLHF pilot

Email us with your use case, domain, and approximate volume. We’ll reply with a pilot scope.

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