Finance AI that can reason, not just retrieve

Proxion delivers expert-sourced training data, evaluations, and benchmarks that help AI systems perform reliably in finance

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Financial AI fails when domain expertise is missing

Tacit by Nature

Financial judgment is built through execution and decision-making under uncertainty, not learned from documents or automated through retrieval

High Stakes by Design

Errors in financial AI carry material consequences. The margin for poor reasoning is zero and the judgment required cannot be crowdsourced

Structurally Complex

Valuation, credit analysis, and capital markets transactions require judgment chains that no annotation platform is built to capture

What Proxion Delivers

Finance-Specific Training Datasets

Built by finance professionals with real execution experience, not crowd annotators

Structured for model training across valuation, credit analysis, equity research, and capital markets

Evaluation Sets and Benchmarks

Scenarios built around how financial decisions are actually made, not adapted from generic benchmarks

Covers financial NLP, numerical reasoning, forecasting, and multi-step decision-making

RLHF and Preference Data

Expert-ranked outputs and preference data used to improve model behavior across financial reasoning tasks

Supports alignment, fine-tuning, regression testing, and production quality assurance

AI Output Grading

Finance professionals review AI-generated outputs for accuracy, rigor, reasoning quality, and methodological soundness

Delivered as structured scoring aligned to institutional finance standards

Human-in-the-Loop Validation

Real-time expert validation for high-stakes financial AI systems operating in production

Adds continuous oversight to advisory tools, risk models, and AI-assisted investment workflows

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

How it Works

From brief to validated delivery in days, not quarters

1

Define the task

Tell us what you need, from training data to benchmarks and evaluations. We establish scope quickly and ensure alignment from day one

2

Scope and structure

We design the task architecture and match it to the right domain experts for your specific requirements, not generic contractors

3

Expert execution

Finance professionals generate structured intelligence using explicit reasoning traces and rubrics designed for your specific domain and use case

4

Model ready delivery

You receive validated, metadata tagged outputs ready for your training or evaluation pipeline, with audit trails, quality review, and delivery in your required format under NDA

Quality & Standards

Our expert network is built from experienced finance professionals with real execution backgrounds across banking, investing, credit, and corporate finance. Every contributor meets a seniority and domain expertise threshold designed for high-stakes financial AI work

Who is in the network

Professionals from bulge bracket banks, elite boutiques, top-tier private equity and credit funds, hedge funds, and institutional asset managers

Baseline seniority

Associate and above, with most contributors at the senior professional level with hands-on institutional experience

Operating standards

All engagements operate under mutual NDAs, enterprise-grade access controls, governed workflows, audit trails, and full output ownership transfers to the client upon delivery

Use Cases

Anonymized scenarios from real engagements

Leading AI Lab

Challenge

A leading AI lab needed expert produced training data for financial reasoning tasks where generic annotation could not capture the level of judgment required

Solution

Proxion delivered structured training data and reasoning traces produced by finance professionals with direct transaction execution experience

Fintech Platform

Challenge

A fintech platform needed expert validation of AI generated investment outputs before surfacing them in a high stakes user environment

Solution

Proxion provided a human in the loop review layer staffed by finance professionals to validate outputs for quality, reasoning, and regulatory compliance

Enterprise AI Team

Challenge

An enterprise AI team needed benchmarks that reflected real financial workflows rather than generic model performance

Solution

Proxion built a custom evaluation suite designed around forecasting, planning, and financial analysis tasks grounded in industry standards

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The next generation of financial AI will be built on real judgment

Tell us what you're building. We'll define exactly what your system needs to reason reliably

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