Graph Database Bengaluru

Tickets are free but mandatory, and can ONLY be issued from the below link: https://lu.ma/69unkg9g
IMP: RSVP here on meetup.com does NOT constitute a ticket​============================================

Join us for an exciting session on the intersection of Generative AI, Retrieval-Augmented Generation (RAGs), Graph Databases, and Large Language Models (LLMs) at Microsoft Reactor, Bengaluru.

You'll learn how Neo4j and GraphRAG are forming the backbone of cutting-edge conversational agents, discover how knowledge graphs can be built from text documents using LLMs, and explore the integration of LangChain with Neo4j's innovative LLM Builder to enhance AI-driven solutions.

Speakers:

1. Ravi Ranjan, Manager Data Science at Publicis Sapient
   Topic: Neo4j and GraphRAG: Building the Backbone of Conversational AI
   Talk Description: In today's rapidly advancing field of conversational AI, integrating knowledge graphs has become essential for enhancing the intelligence and reliability of language models. In this session, we will explore how Neo4j, a leading graph database platform, can be leveraged to construct knowledge graphs that power Graph Retrieval-Augmented Generation (GraphRAG) systems. By transforming unstructured data into interconnected knowledge graphs, GraphRAG addresses common challenges like hallucinations and contextual misunderstandings in AI models, enabling them to provide more accurate and context-rich responses. We will gain practical insights into building and querying knowledge graphs with Neo4j and learn how GraphRAG significantly improves the performance of conversational AI applications.
   Speaker Bio: Hello, I'm Ravi Ranjan. With a foundation in Computer Science, I've spent over ten years as a Data Scientist and Machine Learning Engineer, specializing in AI and ML at the core of enterprise data solutions. My experience spans a variety of industries, including the Automobile, Banking, Retail, and Insurance sectors, delivering AI solutions globally. One of my standout accomplishments is designing a hyper-personalized recommendation system that boosted test drive bookings by an extraordinary 900%. Currently, as a Manager of Data Science, I am focused on developing a scalable GenAI platform for generative content review across various formats of brand assets.
2. Abhishek Mishra, DevRel Engineer at TuneAI
   Topic: Building Knowledge Graphs from Text Documents Using LLMs and Graph Database
   Talk Description: In this talk, we'll explore the intersection of Large Language Models (LLMs) and graph databases - in this case Neo4j, focusing on how to construct rich, interconnected knowledge graphs from unstructured text documents. We'll learn the practical techniques for leveraging the semantic understanding capabilities of LLMs to extract entities and relationships, and demonstrate how to store and query this knowledge graph.
   Speaker Bio: Abhishek Mishra is DevRel Engineer at Tune AI and a Python Software Foundation Fellow. He is community-first person and is an organizer of PyCon India, GDG Chennai, MumPy and many other community initiatives.
3. Alison Cossette, Developer Advocate at Neo4j
   Topic: Practical GraphRAG
   Talk Description: We all know that LLMs hallucinate and RAG can help by providing current, relevant information to the model for generative tasks. But can we do better than just vector retrievals? A knowledge graph can represent data (and reality) at high fidelity and can make this
   rich context available based on the user's questions. But how to turn your text data into graphs data structures?
   Here is where the language skills of LLM can help to extract entities and relationships from text, which you then can correlate with sources,
   cluster into communities and navigate while answering the questions.
   In this talk we will both dive into Microsoft Research's GraphRAG approach as well as run the indexing and search live with Neo4j and LangChain.
   Speaker Bio: Alison Cossette is a Data Science Strategist, Educator, and Developer Advocate at Neo4j, specializing in Graph Data Science. With a strong background in AI and ethical AI practices, Alison bridges complex data concepts with real-world applications. She did Master’s studies at Northwestern University and has conducted research with Stanford's Human-Computer Interaction Crowd Research Collective. Passionate about responsible AI, Alison engages with professionals, policymakers, and the public to promote ethical AI development. She also hosts a podcast, driving innovation and education in data science and AI, making her a respected figure in the field.

============================================
Tickets are free but mandatory, and can ONLY be issued from the below link: https://lu.ma/69unkg9g
IMP: RSVP here on meetup.com does NOT constitute a ticket​

Tickets are free but mandatory, and can ONLY be issued from the below link: https://lu.ma/jvbmuijh
IMP: RSVP here on meetup.com does NOT constitute a ticket​============================================

Join us at Microsoft Reactor, Bengaluru, for an action-packed session diving into Generative AI, RAGs, Graph Databases, and LLMs!

This meetup features three expert-led talks on cutting-edge Conversational AI, Knowledge Graphs, and AI-powered solutions. Discover how Neo4j and GraphRAG are revolutionizing conversational agents, learn to build knowledge graphs from text using LLMs, and explore the seamless integration of LangChain with Neo4j’s LLM Builder to power up your AI applications.

Speakers:

1. Aravind Parameswaran, Co-Founder @ Krux AI
   Topic: Advanced RAG Optimization to make it production-ready
   Talk Description: We explore effective strategies for optimizing your RAG setup to make it production-ready. We will cover practical techniques such as data pre-processing, query expansion & reformulation, adaptive chunk sizing, cross-encoder reranking, Colbertv2 rerankers, Graph RAG etc. to enhance the accuracy of information retrieval in RAG systems. We will also dive into evaluating RAG performance using relevant tools and metrics, providing you with a comprehensive understanding of how to optimize and assess your RAG pipeline.
   Speaker Bio: Aravind Parameswaran is a data & product enthusiast, with 15+ years of experience in data, analytics & product. He’s currently co-founder at Krux AI, makers of the open-source tool RAGBuilder (ragbuilder.io). He has worn multiple hats in his career - analyst, technology architect, data engineer, product manager, and was previously leading cross-functional teams at Cult Fit, and at Meta/ Facebook.
2. Sankalp Srivastava, Founder @ Schematise Lex Data Analysis
   Topic: Exploring Ontologies for Knowledge Graphs
   Talk Description: As part of an ongoing project, Sankalp has been working on simplifying clickwrap agreements such as privacy policies for end users along with his collaborator, Mayank Kumar. The project relies on a novel approach to domain-specific guided Graph creation for automation of the markup process of privacy policies, hence the process of constructing a GraphDB is simplified in this process by relying on a shared ontology itself. The representation of domain knowledge in the privacy field using an ontology to mark up privacy policies for this purpose creates a codebase that will be applicable to any project looking to apply rule-based constraints through a GraphRAG mechanism.
   Speaker Bio: Sankalp is a Legal Tech innovator with over a year's experience in data analysis across various subject areas relating to law and public policy. Soon after switching jobs in the area of legal consultancy and litigation, Sankalp became a self-starter in the field of Legal Tech innovation with apps such as "Schematise" and "Lex Liberalis" and datasets such as "ICAT" being developed by him under copyleft licensing that utilise Legal Ontologies for this purpose. As ontologies work with domain knowledge, Sankalp founded Schematise Lex Data Analysis as a company that seeks to work towards better knowledge representation for Indian laws and public policies.
3. Sterin Jacob, Technical Support Engineer at Neo4j
   Topic: Integrating LangChain with Neo4j: Leveraging Neo4j Labs' LLM Builder
   Talk Description: This demo will showcase how to integrate LangChain with Neo4j to build powerful, knowledge-driven applications.
   We will explore how to use LangChain for intelligent chain-of-thought prompting in combination with Neo4j’s graph database, enabling enhanced query understanding and data retrieval.
   Additionally, we’ll demonstrate the LLM (Large Language Model) Builder from Neo4j Labs, a tool designed to seamlessly integrate LLMs with Neo4j for advanced natural language understanding and generation tasks.
   Speaker Bio: To be updated

***

Whether you're a data scientist, AI engineer, or tech enthusiast, this meetup will provide hands-on insights into how these technologies are converging to power the next generation of AI applications.

Expect engaging discussions, networking opportunities, and the chance to deepen your understanding of how these transformative technologies can be applied to real-world problems.

============================================
Tickets are free but mandatory, and can ONLY be issued from the below link: https://lu.ma/jvbmuijh
IMP: RSVP here on meetup.com does NOT constitute a ticket​