Client: Large Enterprise with Complex Documentation Needs
The Challenge
The client struggled with knowledge management, as employees found it difficult to retrieve relevant documents quickly.
The Solution
- Developed a Retrieval-Augmented Generation (RAG) model using LLMs (GPT-4) and Pinecone Vector Database.
- Implemented semantic search to fetch the most relevant documents based on queries.
- Integrated with the enterprise knowledge base and internal documentation systems.
- Developed a chat-based interface for employees to ask complex queries and retrieve contextual responses.
The Results
- 70% reduction in search time for documents.
- Increased productivity by 40%.
- Enhanced knowledge retention and access to critical information in real-time.
