Demo

Enabling Gen AI-powered conversational experiences on enterprise content

GenAI fabric

In this demo, we will showcase how, using Gathr’s GenAI fabric, you can build a GenAI-powered chatbot to enable your employees to interact with your enterprise knowledge base, get answers to their questions, and in-turn improve their productivity and business impact.

We’ll build the chatbot using the RAG framework, which integrates domain-specific knowledge and addresses challenges like hallucination in large language models (LLMs).

First, we’ll build a data engineering pipeline to fetch data from various enterprise sources, parse it, generate embeddings, and then ingest it into the vector database. Post that, we will develop a frontend application that allows employees to get relevant answers, instantly, by augmenting the LLM with the vector database.

Key demo takeaways:

  • Build RAG based chatbot for production
  • Collect and prepare the data for embeddings
  • Populate vector database, integrate it with LLM
  • Build the chatbot application for employees
  • Monitor and improve the chat prompts

Watch Now

I agree to the processing of the data by Gathr Data Inc as described in the Privacy Policy. I also provide my consent to be contacted by the company's representatives.

Related demos

View more demos

Demo

Building Gen AI powered recommendation engine
GenAI fabricHealthcare

Demo

Building Gen AI powered entity extraction solution
GenAI fabricHR & recruitment