The situation
The fintech company wanted to use LLMs on sensitive financial data, but compliance and confidentiality meant nothing could be sent to third-party APIs. It also needed to control the rising cost of high request volumes.
What we did
We set up and optimized a local Llama 3.1 deployment served with vLLM, containerized with Docker on NVIDIA GPUs, with Redis caching for throughput. The whole stack runs inside the company's own infrastructure.
The outcome
100% of data stays in-house, API costs dropped by 90%, and the system comfortably handles 10,000+ requests a day.