- Engineered a multimodal GraphRAG using
- Neo4j, LlamaIndex, and Langchain, and prompt engineered
- AWS Bedrock
- Anthropic Claude v3.5, enhancing the creation of complex service documentation from audio, visual and textual data
- Leveraged Advanced RAG with Metadata Filtering, Hybrid Search, LLM re-ranking, and in-context learning, to improve the response relevancy by 26% and drive customer satisfaction
- Incorporated streaming integration with the UI using FastAPI and NextJS, reducing the response time from 10s to under 2s
- Processed and clustered conversational data stored in Amazon S3, extracted semantically rich FAQ's for customer support
- Designed and implemented a playlist expansion Recommendation System, experimenting with and optimizing 3 Graph
- Neural Network architectures, deploying the optimal model and contributing to 17% of the projected annual revenue
- Generated and uploaded the Docker image to Amazon ECR and used Fargate container orchestration
- Deployed the applications to AWS Lambda