How a leading US neobank reduced customer support resolution time by 62% using FloTorch's RAG blueprints

The Challenge

A fast-growing US neobank was seeing a 40% year-over-year surge in support tickets — most of them repetitive, document-level queries about account policies, transaction limits, and compliance FAQs. Without an ML team, building a custom RAG system from scratch wasn't an option. Previous off-the-shelf chatbot attempts had resulted in hallucinated responses, creating compliance risk and eroding team confidence in AI-assisted support entirely.

The Solution

1 Document ingestion — 80,000 pages of policy documentation chunked and embedded using FloTorch's no-code ingestion interface.

2 Pre-launch evaluation — Blueprint Evaluator ran 1,200 test queries, catching accuracy issues before any customer interaction.

3 Guardrails configured — Hallucination and PII protection enabled to restrict the assistant to verified document content only.

4 One-click deployment — Live in production on Day 4, embedded into the existing support portal via API. Zero DevOps required.