Domain-specific datasets for post-training evaluation and agent reasoning
Research-grade datasets and evaluation resources across finance, legal, medical, and economics domains.
Domain-specific datasets
Curated QA and reasoning tasks across specialized fields, built for depth, accuracy, and domain fidelity.
Applied Reasoning in Business, Law, and Finance
Clinical and Biomedical QA
Visual QA and Non-STEM Domains
Benchmarks and evaluation
Research-grade benchmarks and diagnostics built to surface failure modes and measure verified performance in domain-specific systems.
SWE-bench++
VLM-bench
Domain-Aware Reasoning Audit
RL environments for domain-specific reasoning
Evaluate reasoning agents on real-world finance, economics, legal, and medical tasks, generate fine-tuning trajectories, and train reward models in reproducible, high-fidelity environments.
UI-Based RL Environments for Interface Agents
MCP Environments for Function-Calling Agents
End-to-End Evaluation and Training Loops
Research and case studies
FAQs
What domains do Turing's evaluation datasets cover?
Turing offers datasets and data packs across finance, legal, medical, economics, business, clinical and biomedical, visual QA, and non-STEM domains.
What types of tasks are included in Turing's domain-specific datasets?
The datasets include complex QA tasks, applied reasoning scenarios, diagnostic reasoning, treatment mapping, visual reasoning tasks, and structured decision-making prompts grounded in real-world contexts.
What is SWE-bench++?
SWE-bench++ is a benchmark that evaluates coding agents on real GitHub tasks using containerized environments and verified trajectories.
What does VLM-bench measure?
VLM-Bench is Turing’s benchmark for vision-language reasoning, covering more than 700 tasks across STEM, logical inference, spatial reasoning, and real-world multimodal problem-solving.
What are RL Environments for domain-specific reasoning?
Turing's RL Environments for domain-specific reasoning are reproducible settings where agents can solve tasks in finance, legal, medical, and economic domains. They support evaluation, trajectory generation, and structured improvement inside high-fidelity workflows settings across finance, economics, legal, and medical domains.
What types of RL Environments does Turing offer?
Turing provides UI-based RL Environments for interface agents and MCP environments for function-calling agents, each with domain APIs, verifiers, and structured evaluation pipelines.
How can Turing's datasets improve domain-specific LLM performance?
Turing’s research-grade datasets surface failure modes, support evaluator calibration, enable structured reward-based improvement, and provide expert-reviewed reasoning traces that strengthen accuracy and robustness in specialized domains.
Can I request custom domain-specific datasets from Turing?
Yes. Turing can provide custom domain-specific data packs and evaluation environments. You can request tailored datasets or environments through our contact form.
Accelerate domain-specific reasoning with Turing
From tax code to triage, our data helps you train and evaluate models with high-stakes reasoning in mind.
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