From hard questions to reviewable model evidence
Cases span STEM, finance, legal, medical, agents, machine learning, software engineering, geoscience and education. Explore task goals, working methods, reference artifacts and acceptance evidence across specialist domains.
Workbench visuals are domain-specific UI concepts. Open each case for delivery methods and original workflow films.

Financial reasoning with source evidence
Research, valuation, risk and compliance judgments delivered with answers, evidence, boundaries and review state.

Legal review with citation-level evaluation
Verifiable tasks across contracts, regulations and case material—not unsupported conclusions.

Medical evidence abstraction and safety evaluation
Literature, guidance and case-style material converted into structured evidence, references and safety boundaries.

Expert-authored STEM challenge sets
Original tasks that combine advanced knowledge, multi-step derivation and verifiable answers beyond direct retrieval.

Long-horizon agent trajectories and failure attribution
Node-level review from task intake and planning through tool use and final deliverables.

MLE-Bench / MLS-Bench-style evaluation operations
Evaluate task completion, experiment reproducibility, method improvement and evidence of generalization.

Executable program-reconstruction evaluation
Models receive behavioral specifications and a black-box reference, then rebuild a complete compatible program against hidden tests.

Long-horizon repository engineering evaluation
Repository exploration, multi-file implementation, regression protection and environment verification organized as adjudicable long-horizon work.

Multi-source geoscience interpretation and synthesis
Well, interval, map, report and historical interpretations connected into traceable specialist reasoning tasks.

Curriculum-grounded authoring and learning diagnosis
Curriculum standards, concept dependencies, original items and explainable scoring organized as reliable education-model data.
Cases use representative sanitized delivery structures. Client identities, source content and selected volumes have been removed or banded to explain operating methods and prior delivery experience; results are not guarantees of future performance.
Build data around your next capability goal
Start with a task goal and a sample. Define the materials, specialists, verification methods and delivery scope together.
