This is a simple RAG demo for a bank's customer support bot, for use with the Multinear platform.
This project shows how simple it is to build a proof-of-concept using RAG for a customer support bot answering user questions on FAQ data, with platforms like LangChain.
The real challenge is to ensure that this bot is reliable - always giving the right answer, not hallucinating, and knowing how to deal with ambiguous or off-topic questions. GenAI is a powerful technology, but it's also unpredictable by design, and the only way to make it reliable is to build comprehensive test coverage and guardrails.
That's exactly what the Multinear platform is for. Multinear allows developers to define evaluations in a simple yet powerful way and iteratively develop their GenAI applications, ensuring reliability and security.
The AI Researcher
Demo Bank Customer Support
This is a simple RAG demo for a bank's customer support bot, for use with the Multinear platform.
This project shows how simple it is to build a proof-of-concept using RAG for a customer support bot answering user questions on FAQ data, with platforms like LangChain.
The real challenge is to ensure that this bot is reliable - always giving the right answer, not hallucinating, and knowing how to deal with ambiguous or off-topic questions. GenAI is a powerful technology, but it's also unpredictable by design, and the only way to make it reliable is to build comprehensive test coverage and guardrails.
That's exactly what the Multinear platform is for. Multinear allows developers to define evaluations in a simple yet powerful way and iteratively develop their GenAI applications, ensuring reliability and security.
@GitHub https://github.com/multinear-demo/demo-bank-support-lc-py?tab=readme-ov-file
1 month ago | [YT] | 1