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Generate eval rubrics & training datasets from human behavioral data

Auto-generate evaluation rubrics and training datasets based on mined human behavioral data of how your human experts actually perform their daily work.

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The platform

Evals & scoring

Evaluations, rubrics & reward models

Evaluations, rubrics & reward models

Evaluation rubrics

Auto-generate evaluation rubrics & scoring datasets in customizable schemas for your use cases based on how your human experts perform their daily tasks & workflows.

SFT, DPO, and RLHF

Training datasets

Auto-generate training-ready SFT, DPO, and RLHF datasets based on mined human behavioral data of how your human experts actually perform their daily work.

Make your models think, act, and behave like your human experts

Step 1

Human behavioral data mining from experts

Lanturn mines all raw event data of human/domain experts performing their regular day-to-day workflows & tasks.

Workflow 1

1,153 events captured

Step 2

Enrichment & labeling of human behavioral data

Our real-time labeling & enrichment models turn raw human behavioral event data into structured intelligence.

Enriching..

Step 3

Auto-generate eval rubrics, SFT, DPO, and RLHF datasets

Our models turn the enriched & labeled human behavioral data into ready-to-use eval rubrics, SFT, DPO, and RLHF datasets.

  {
  "rubric_type": "score_rubric",
  "task_id": "gdpval-law-enforcement-uas-policy-2025",
  "task_title": "Law Enforcement Drone (UAS) Policy — Score Rubric",
  "version": "1.1",
  "score_scale": [0, 1, 5, 8, 10],
  "columns": [
    { "label": "Unacceptable", "points": 0 },
    { "label": "Poor", "points": 1 },
    { "label": "Acceptable", "points": 5 },
    { "label": "Good", "points": 8 },
    { "label": "Excellent", "points": 10 }
  ],
  "evaluation_instructions": {
    "role": "Policy evaluator or law-enforcement subject matter expert",
    "objective": "Assess the completeness, professionalism, and procedural accuracy of the model-generated police drone policy using a five-tier (0–10 point) qualitative scale. Each level corresponds to increasing policy maturity and compliance with real-world law enforcement manual standards.",
    "scoring_guidance": {
      "10": "Fully professional and adoption-ready. Mirrors exemplary PD policy with no factual or structural errors.",
      "8": "Strong

Fuel your models & AI agents with human behavioral intelligence

Executable eval rubrics from real work, not grader opinion

Instead of hand-written checklists and noisy manual scoring cards on third-party interpretations of the use cases of your eval rubrics, we convert data of how experts actually do their work into executable tests — so you get high quality ground truth eval rubrics for prime model performance, not rater opinion.

Executable eval rubrics from real work, not grader opinion

Instead of hand-written checklists and noisy manual scoring cards on third-party interpretations of the use cases of your eval rubrics, we convert data of how experts actually do their work into executable tests — so you get high quality ground truth eval rubrics for prime model performance, not rater opinion.

Process-linked reward modelling (anti-reward hacking RLHF fuel)

Rewards intermediate actions that move toward the goal or reflect good reasoning and include negative signals for violations. This mitigates reward hacking and aligns optimization with real KPIs, not proxy scores.

Behavior-grounded static labels & annotations

The system labels & annotates static data based on how experts actually interact with them in real-world workflows instead of static, context-free guesses from screenshots, specs, or crowd annotators looking at the data in isolation.

Behavior-grounded static labels & annotations

The system labels & annotates static data based on how experts actually interact with them in real-world workflows instead of static, context-free guesses from screenshots, specs, or crowd annotators looking at the data in isolation.

2X richer SFT/DPO/RLHF training datasets for your models

Lanturn's data captures not just outcomes but the decision-making steps behind them. This provides models with the reasoning, context, and decision-making patterns missing from synthetic or static datasets.

Make models & agents adopt your way of working

AI models & agents force teams to adapt to their limitations & have fixed ways of working. Lanturn trains your agents on your team's actual workflows so they naturally work the way you do.

Make models & agents adopt your way of working

AI models & agents force teams to adapt to their limitations & have fixed ways of working. Lanturn trains your agents on your team's actual workflows so they naturally work the way you do.

Turn black box reasoning into predictable & consistent behavior

Your models & agents operate like a black box, making hidden decisions that are hard to predict or control. Lanturn turns opaque reasoning into consistent, correct, and repeatable behavior.

Start leveraging human behavioral data

Get a demo

Get a demo