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Research

Financial AI you can audit.

Our research program exists to answer one question: how do you make an LLM trustworthy enough to sit inside a CFO's workflow? Everything else follows from that.

Research pillars

Source traceability

Every output is grounded in a citation to the underlying record. We research retrieval and attribution methods that make this the default, not an add-on.

Financial reasoning

Models purpose-trained on financial and market data, benchmarked against hallucination and numerical-consistency tests specific to finance.

Human oversight

Research into interfaces and workflows that keep sensitive financial actions subject to human review, without slowing teams down.

Reproducibility

Same input, same output, same citations. We treat reproducibility as a safety property, not a nice-to-have.

100%
Source-traceable outputs
7+
Financial reasoning benchmarks
0
Training on customer data

Read what we've published.

Technical reports and benchmark results from the research team, updated as work ships.