Generalist contributors
High-volume, well-defined tasks such as categorization, simple preference judgments, basic validation and collection workflows.
Add human expertise
Put the right human judgment where automation stops being enough.
Route training, evaluation, language and multimodal work to qualified reviewers, from generalist contributors and linguists to domain specialists and QA leads.
Human review routingactive queue
Incoming taskambiguous financial answer
Generalistclear casesDomain expertbest fitAdjudicatorescalations
Routed with contextrisk · domain · rubric attached
QualifiedRole-fit before routing
CalibratedGold tasks set the bar
EscalatedAdjudicate the hard cases
Built around the real work
Capabilities that move a model from promising to useful.
Choose the parts of the data and quality workflow that match the behavior, market or modality you are building for.
BUILD
Designed for the next decision, not the last task.
Every capability is shaped around downstream use: what the model needs to learn, what reviewers need to judge and what your team needs to ship with confidence.
Talk through your workflow01
Linguists & native speakers
Translation, localization, transcription, fluency review, terminology, dialect authenticity and multilingual evaluation.
Domain specialists
Legal, technical, financial, healthcare and other expert tasks where correctness requires subject-matter knowledge.
Creative & writing experts
Style-sensitive generation, editing, response preference, tone evaluation and human-authored demonstrations.
Safety & red-team reviewers
Policy-aware adversarial testing, harmful-content classification, edge-case generation and escalation workflows.
QA leads & adjudicators
Calibration, gold-set design, reviewer monitoring, disagreement resolution and rubric improvement.
Review queueContext-aware routing
Generalistclear instructionready
Linguistlocale nuancereview
Domain experthigh-risk caseassigned
Adjudicatordisagreementstandby
Judgment is routed with the rubric.Qualification, calibration and escalation are part of the system.
Expertise has to be verified
Use experts to create, judge, correct and challenge the model.
Quality improves when contributor selection is part of workflow design. Build qualification and ongoing performance into the project as guidelines and model behavior change.
- Route ambiguity, domain and risk to the right tier
- Keep gold examples and calibration visible
- Use disagreement as a signal for rubric improvement
The operating model
A human-in-the-loop system that learns the rubric.
Qualification is the starting point; calibration and adjudication keep quality aligned in production.
Qualify
Match language, domain, task and experience requirements before work begins.
Train
Introduce project guidance, examples, edge cases and the quality bar.
Calibrate
Use gold tasks and a pilot batch to align reviewers before production.
Monitor
Track agreement, performance, disagreement and escalation signals.
Adjudicate
Resolve hard cases, update guidance and recalibrate the reviewer group.
Quality that holds up in production
Focus experts on the expensive mistakes.
Use generalists where instructions are objective and experts where a plausible-sounding answer can still be materially wrong without specialist knowledge.
- Detailed rubrics, examples and calibration rounds
- Agreement analysis, escalation and adjudication
- Ongoing feedback instead of one-time training
CreateExpert demonstrations, SFT responses, preference and critique records
JudgeModel, agent, multilingual, transcription and multimodal evaluation
ChallengeRed-team scenarios, adversarial prompts and policy edge cases
ControlQualification, gold sets, QA monitoring and adjudication history
What arrives at the end
Deliverables your team can use.
Clear outputs, stable structure and the context needed to move the work into training, evaluation or production.
01Qualified reviewer or expert profile
02Project training and calibration records
03Expert demonstrations and reference answers
04Preference, critique and rewrite judgments
05Domain and multilingual evaluation
06Red-team findings and safety cases
07QA and agreement reporting
08Adjudication decisions and guideline updates
Where it fits
Post-training data
Produce high-quality demonstrations and preference judgments.
Specialist evaluation
Apply domain-specific rubrics to technical, legal, healthcare or financial tasks.
Agent evaluation
Judge tool decisions, trajectories, recovery and completion.
Synthetic validation
Check factuality, diversity, realism and guideline compliance before training.
Start with the outcome
Build a human layer around the work automation cannot judge reliably.
Tell us the task, domain, language, ambiguity and risk. We’ll define the reviewer profile, qualification, calibration and QA workflow around it.