Domain Data Sprints
Target the exact failures hurting quality
Rapid, focused data generation sprints that produce high-quality training data specifically designed to address your model's weak points. Expert-authored, evaluation-grade datasets your team owns.
SME-authored SFT / preference / reasoning data targeted to your failure modes.
Methodology: Our Sprint Methodology
Rapid, focused data generation that targets exactly what your model needs. Our SME-authored datasets are designed to fix specific failure modes, not just add volume.
- Failure mode analysis
- SME-authored examples
- Multi-layer QA process
- Iterative refinement
Modules & Capabilities
SFT (Instruction Tuning) Packs
Domain-specific writing and formatting examples
Preference / Ranking Data
Pairwise comparisons aligned to your rubric criteria
Reasoning & Decision Data
Structured justifications with traceable decision logic
Prompt + Rubric Library Build
Foundation artifacts your team reuses across projects
Edge-Case Harvesting
Active search and generation of corner cases
Results: Targeted Model Improvements
Our data sprints deliver measurable improvements in the specific failure modes you care about most, with data your team owns and can reuse.
- Failure mode reduction
- Training data ownership
- Reusable prompt libraries
- Clear improvement metrics
Deliverables
- Task spec + schema
- Training dataset batch + dataset card
- QA report (defect rate, adjudication outcomes)
- Next batch recommendations based on failures
Get started with Domain Data Sprints - contact our team for a scoping call.