This system turned natural-language business questions into safe analytical workflows supported by query generation, entity resolution, and semantic cache layers.
The goal was not only to generate SQL. It was to make conversational analytics predictable, cheap enough to scale, and fast enough to be used regularly.
What was built
- NLP-to-SQL orchestration layer
- semantic and exact-match caching
- entity resolution and schema-aware retrieval
- chart generation and contextual follow-up flows
Why it mattered
The most important result was not just capability. It was operational economics.
Faster cache hits reduced expensive end-to-end execution and created a clearer path to scale. This is now a core NewCo360 offer for analytics teams that need production-ready conversational access to data.