Tell us what you’re building
We’ll review your requirements and show how expert sourced financial intelligence improves outcomes
Every dataset, evaluation, and benchmark Proxion delivers is grounded in real experience from the highest levels of global finance
Where Proxion experts come from
Bulge bracket banks, elite boutiques, and top-tier private equity, credit, and hedge fund platforms
Seniority floor
Associate and above, with most contributors at the senior level and direct hands-on institutional experience
Why it matters
Financial AI requires reasoning quality, not annotation volume. The difference between a model that retrieves and one that reasons comes from domain experts with real transaction experience
How we can work together
Finance Specific Training Datasets
- Expert-produced datasets for financial reasoning tasks that generic annotation cannot replicate
- Structured to your exact format: instruction pairs, preference data, reasoning traces, or custom schemas
- Full audit trails and metadata included
Evaluation Sets and Benchmarks
- Domain validated scenarios designed to measure model performance against real financial standards
- Covers financial NLP, numerical reasoning, forecasting, and multi-step decision making
- Built with active participation from finance professionals
RLHF and Preference Data
- Expert-ranked outputs and preference data for model fine-tuning across financial reasoning tasks
- Supports alignment, fine-tuning, regression testing, and production quality assurance
- Delivered in formats aligned to your pipeline
AI Output Grading
- Expert review of AI generated financial outputs for accuracy, rigor, and methodological soundness
- Delivered as structured scoring aligned to institutional finance standards
- Covers financial analysis, investment recommendations, risk assessments, and modeling outputs
Human in the Loop Validation
- Real time expert validation for high stakes financial AI systems operating in production
- Supports financial advisory tools, risk models, and AI assisted investment workflows
- Delivered under NDA with enterprise grade data governance
Red Teaming and Adversarial Stress Testing
- Finance specific adversarial testing designed to surface model weaknesses before deployment
- Identifies failure modes across edge cases, out of distribution inputs, and complex decision scenarios
- Delivered with detailed failure reports and recommendations for model improvement
All engagements operate under mutual NDAs
Data handled under enterprise-grade security protocols
Full output ownership transfers to client on delivery