Reasoning Data Studio

Improve multi-step correctness—not just fluent answers

Many AI systems fail not because they lack knowledge, but because they make unsupported leaps, skip constraints, or miss edge cases in complex workflows. ProofLab Reasoning Data Studio produces expert-authored reasoning datasets and evaluation suites that improve reliability in multi-step decision making.

Build evaluation-grade reasoning datasets with chain-of-thought, structured rationales, and decision traces.

Methodology: Our Reasoning Data Methodology

We create training data that teaches models to think step-by-step. Our reasoning traces are expert-authored with verifiable logic chains.

  • Chain-of-thought annotation
  • Logic verification
  • Decision tree mapping
  • Error pattern analysis

Modules & Capabilities

  • Reasoning Dataset Builds

    Troubleshooting flows, eligibility decisioning, multi-step planning, and structured outputs

  • Chain-of-Thought Programs

    CoT for internal improvement, structured rationales for production, decision trace formats

  • Reasoning Evaluation Suites

    Benchmarks measuring correctness, constraint adherence, logical consistency, and grounding

  • Failure Mode Mining

    Adversarial rephrasings, ambiguous evidence scenarios, exception-heavy cases, OOD variants

Results: Superior Reasoning Capabilities

Models trained on our reasoning data show measurable improvements in logical accuracy and explanation quality.

  • Better chain-of-thought
  • Verifiable logic
  • Reduced hallucination
  • Traceable decisions

Deliverables

  • Reasoning dataset batch (CoT / structured rationale / decision trace)
  • Task specification + schema + formatting constraints
  • Rubric and scoring guide (binary + graded)
  • Calibration set with adjudicated gold examples
  • Benchmark report: score breakdown, top failure modes, prioritized fixes

Get started with Reasoning Data Studio - contact our team for a scoping call.