Cover Image for Virtual  Lunch & Learn: RAG to GraphRAG — Smarter AI Retrieval
Cover Image for Virtual  Lunch & Learn: RAG to GraphRAG — Smarter AI Retrieval
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ApertureData
Graph-vector database purpose-built for multimodal AI
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Virtual Lunch & Learn: RAG to GraphRAG — Smarter AI Retrieval

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​Virtual Lunch & Learn: RAG to GraphRAG — Smarter AI Retrieval

Details:

📅 Tuesday, August 26, 2025
🕘 11:00–  12:00 PM | PDT
🎙️ Featuring Ayesha Imran—Associate Engineer, Data Science Dojo  & Gautam Saluja— Sr Software Engineer, ApertureData
​👉 Save Your Spot

​Grab your lunch and join us for this virtual Lunch & Learn!

In this session, our community member Ayesha Imran will show how to go beyond Vanilla RAG by automating GraphRAG—merging semantic embeddings with knowledge graphs for smarter AI retrieval.”

​Drawing from her popular 4-part blog series, Ayesha will walk you through how to:

  • ​Automate knowledge graph creation with Google Gemini + ApertureDB.

  • ​Add semantic layers for hybrid GraphRAG retrieval.

  • ​Benchmark GraphRAG vs. Vanilla RAG with both quantitative metrics and LLM-as-a-judge qualitative evaluation.

  • ​Understand when graph context beats pure similarity search

​What you’ll learn:

  • ​Why GraphRAG retrieval delivers smarter, more connected answers than traditional RAG.

  • ​How to build an AI-ready knowledge graph pipeline from raw PDFs to production—without manual glue code

  • ​Practical trade-offs: precision, cost, and explainability

​Who should attend:

AI engineers, data scientists, ML researchers, and anyone working on LLM-powered applications who want  to improve retrieval quality, reduce hallucinations, and build smarter AI systems.

​👉 Register now to secure your spot!

💻 Follow along live with the Colab notebooks:
Part 1 & 2
Part 3
Part 4

​Can’t make it to the Lunch & Learn?
We’ve got you covered. Register and we will send you a link with the replay once it is available.

Avatar for ApertureData
Presented by
ApertureData
Graph-vector database purpose-built for multimodal AI
Hosted By
77 Went