Name: GraphRAG Unleashed: Supercharging LLMs with Knowledge Graphs
Start: 2024-11-20T10:00:00.000Z
End: 2024-11-20T12:00:00.000Z
Location: Room2F | Events & Gallery Space

Inscriptions sur ce lien : [https://go.neo4j.com/LE241112GraphTalkParis_Registration.html ](https://go.neo4j.com/LE241112GraphTalkParis_Registration.html )

Rejoignez-nous pour une matinée passionnante dédiée à l'exploration des innovations en matière de digital twin, de gestion de la supply chain et bien plus encore. Découvrez comment Neo4j, leader mondial des bases de données de graphes, transforme ces secteurs critiques grâce à la puissance des graphes.
Que vous soyez un expert de la technologie ou que vous débutiez dans ce domaine, cet événement vous apportera des insights pratiques, des démonstrations en direct et des opportunités de réseautage avec des professionnels du secteur.

**PROGRAMME**
09:30 Accueil Café
10:00 Mot de Bienvenue
10:10 L'art du Possible avec Neo4j - Adrien Boulad
10:40 Cas d'usage Swiss Life - Léa Boussekeyt, Data Scientist, Swiss Life
11:10 Pause Café
11:30 Démonstrations
\- Démo supply chain \- Nicolas Rouyer
\- Démo digital twin \- Pierre Halftermeyer
12:15 Déjeuner & Networking

Inscriptions : [https://go.neo4j.com/LE241112GraphTalkParis_Registration.html ](Inscriptions : https://go.neo4j.com/LE241112GraphTalkParis_Registration.html )

Graph Database - France

Neo4j

Karima

GraphTalk Paris

Comet Meetings - Etoile

Anmeldung: [https://4142298.xyz/de-DE/jug-hamburg/events/304286620/ ](https://4142298.xyz/de-DE/jug-hamburg/events/304286620/)

Lokale Nachrichtenportale werden schnell übersehen oder belächelt. Oftmals kennt und nutzt man sie aber dann doch! In meinem Beispiel liegt das auch daran, dass man dort anonym Kommentare schreiben und sich demnach trefflich über den Unsinn anderer Leute amüsieren oder wahlweise ärgern kann. Aus dem großen Vorbild vom SpiegelMining Vortrag von David Kriesel und der Faszination mit diesem ganz bestimmten Portal ist ein Hobbyprojekt entstanden, von dem ich gern berichten will: Wie sammle ich die Daten, die ich aufnehme? Welche Analysen können wir damit machen? Welchen kreativen Nutzen können die Daten noch haben? Und warum nutze ich für all das (ja, auch das Crawlen!) nur eine **Neo4j** Datenbank?

**Referent**:
Sascha Peukert ist seit 2017 Entwickler bei Neo4j. Dort arbeitete er an der Abfragesprache Cypher und später an Features wie role-based Access Control und fine-grained Security. Seit 2021 arbeitet er an Neo4j Ops Manager, das bei der Administrierung und dem Monitoring von Neo4j Instanzen unterstützt. Aktuell fokussiert sein Team sich darauf diese Funktionen auch in der Cloud für AuraDB bereitzustellen.

Graph Database - DACH (Germany, Austria, Switzerland )

Victor Gras

Igor Akkerman

Ein Tauchgang in den Sumpf eines lokalen Nachrichtenportals

Code Working Space GmbH

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

Graph Database Bengaluru

Mohd Mujtaba

Madhu P

GenAI Convergence: RAGs, Graphs, and LLMs

Microsoft Reactor Bengaluru

Discover HybridAGI, a groundbreaking Cypher-based neuro-symbolic AGI designed to make AI adaptable, reliable, and knowledge-driven. With the power of graph technology, HybridAGI goes beyond traditional Agent systems by using a graph interpreter that dynamically reads, writes, and executes graph-based data, enabling self-programming and on-the-fly adaptation.

Tune in to explore how HybridAGI combines graph and LLM capabilities, allowing users to create secure, memory-centric AI applications with deterministic behavior and extensive customization through Cypher.

Guest: [Laëtitia Del Banio](https://www.linkedin.com/in/laetitiadelbanio/)
HybridAGI: [https://github.com/SynaLinks/HybridAGI ](https://github.com/SynaLinks/HybridAGI)

Graph Database Stockholm

Neo4j Live: HybridAGI – Graph-Powered, Self-Programmable AI

Online event

Join us for an exciting deep dive into the world of GraphRAGs—where knowledge graphs meet the cutting-edge power of large language models (LLMs). In this interactive session, we'll explore how integrating Neo4j with generative AI technologies can drastically enhance the accuracy and reliability of AI-driven insights.

**The agenda of the evening would be:**
\- 6pm: doors open
\- 6\.30pm: announcements and welcome
\- 6\.40pm: 1st Talk
\- 7\.10pm: 2nd Talk
\- 7:40pm: Networking
\- 8\.10pm: doors close

**Speaker:**
🎤 Alison Cossette, Developer Advocate at Neo4j
**Talk 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.

🎤 Bryan Lee, Consulting Engineer @ Neo4j
**Talk topic :** Neo4j Meets Agentic RAG: Enhancing AI with Graph-Powered Retrieval
**Description :** Enter Agentic GraphRAG: a system where LLMs, powered by autonomous agents, intelligently retrieve, correlate, and navigate complex, multi-step reasoning tasks with the help of knowledge graphs.
In this talk, we’ll explore how knowledge graphs, like those in Neo4j, can enhance RAG by providing a high-fidelity representation of entities and relationships extracted from text. You’ll learn how AI agents leverage these graphs to improve the depth and accuracy of responses, enabling true understanding of context and nuanced data relationships.
**Bio :** Bryan Lee is a forward-thinking Consulting Engineer and Data Architect at Neo4j, specializing in GenAI and data-driven solutions. His expertise in optimizing data engineering processes for GenAI applications has driven significant business outcomes, particularly in the ASEAN region.
Bryan’s hands-on approach to problem-solving, combined with his passion for learning, has enabled him to lead innovative deployments in the rapidly evolving field of AI. He frequently shares his knowledge at workshops, conferences, and summits, advocating for the transformative power of GenAI and graph technologies. Bryan is dedicated to helping enterprises unlock their potential by navigating the complexities of data architecture and AI implementation.

**Interested to speak at this or future meetups? Fill this form:** [https://dev.neo4j.com/submit-your-talk](https://dev.neo4j.com/submit-your-talk)

You’ll discover how GraphRAGs (Graph-enhanced Retrieval-Augmented Generation) allow LLMs to go beyond simple text-based search and tap into complex, connected data for more factual and context-aware responses. Don’t miss this opportunity to network with like-minded professionals and take your AI projects to the next level!

Graph Database Singapore

Jo San

Aamir Syed

GraphRAG Unleashed: Supercharging LLMs with Knowledge Graphs

 Room2F | Events & Gallery Space

Neo4j MeetUp

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Connect with our diverse Neo4j community: software engineers, data scientists, mathematicians, and academics. We're for anyone interested in learning about and working with graph databases for social, spatial, hierarchical, or other highly connected data sets. We host hands-on lab sessions, technology reviews, topical lectures, and plenty of social beer nights. Curious about graphs or noSQL tech? Join us! 


Learn about LLMs + Knowledge Graphs, RAG and more

Free Hands-on Online Training

A Practitioner’s Guide by Jesús Barrasa & Jim Webber

Neo4j MeetUp

Neo4j MeetUp

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스폰서

Free Hands-on Online Training

Building Knowledge Graphs

Free Hands-on Online Training

Building Knowledge Graphs

Free Hands-on Online Training

Building Knowledge Graphs

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