BETA RELEASE

Summary

Case study on Kepler Finance using Claude to create a verifiable AI research platform for financial services, combining LLM reasoning with deterministic infrastructure.

Key quotes

On our workloads, Claude was the model that consistently held the plan together
Prompt engineering optimizes a call while content engineering optimizes the system around it.
In finance, the model can’t be the whole system.

Kepler Finance utilizes a multi-stage pipeline incorporating Claude Opus 4.7 for complex reasoning and Sonnet 4.6 for high-throughput tasks. The system integrates a proprietary ontology and deterministic execution environments to ensure financial data is provably correct and auditable.