NEW

Beta: Automated eval generation engine

Beta: Automated eval generation engine

NEW

Beta: Automated eval generation engine

Beta: Automated eval generation engine

Automated evals & training datasets from human behavioral data

Unlock the human behavioral data layer for evals, SFT, DPO, and RLHF datasets by mining how experts perform their daily work.

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The platform

Evaluations & Scoring

Evaluations, rubrics & reward models

Evaluations, rubrics & reward models

Auto-generated evaluation and scoring datasets based on how your human experts perform their daily work

Lanturn auto-generates evaluation & scoring datasets in customizable schemas for your use cases based on how your experts perform their daily tasks & workflows.

SFT, DPO, and RLHF

Auto-generated SFT, DPO, and RLHF datasets based on how your human experts work and interact with your data

Lanturn auto-generates training-ready SFT, DPO, and RLHF datasets based on how your human experts work and interact with your static data.

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 experts/professionals 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 evals, SFT, DPO, and RLHF datasets

Our models turn the enriched & labeled human behavioral data into training-ready evals, SFT, DPO, and RLHF datasets.

{
  "trace_id": "sales-reply-001",
  "workflow": "Sales AI Agent – Generate Email Reply to Prospect",
  "task": "draft_sales_email_reply",
  "prompt": "Generate an email reply to the prospect from ACME Corp who expressed interest in purchasing Compliance Suite Enterprise.",
  "context": {
    "prospect_name": "ACME Corp",
    "product_interest": "Compliance Suite Enterprise",
    "deal_stage": "Post-demo",
    "notes": "Prospect mentioned interest in Enterprise plan during last demo call. Budget confirmed for Q4."
  },
  "gold_outputs": [
    "Hi ACME Corp team, thank you for your interest in Compliance Suite Enterprise. Based on your confirmed budget and our previous discussion, the next steps are to review the pricing package and schedule a follow-up call this week."
  ],
  "success_criteria": [
    "Mentions prospect by name (ACME Corp)",
    "References product (Compliance Suite Enterprise)",
    "Includes relevant CRM context (budget confirmed, interest in Enterprise plan)",
    "Proposes clear next steps (pricing review, follow-up call)",

Fuel your models & AI agents with human behavioral intelligence

Executable evals from real work, not grader opinion

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

Executable evals from real work, not grader opinion

Instead of hand-written checklists and noisy manual scores based on third-party interpretations of the use cases of your evals, we convert data of how experts actually do their work into executable tests — so you get high quality ground truth evals 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