Graph Database Mumbai

As GenAI moves from hype to implementation, many teams struggle to bridge the gap between impressive PoCs and reliable, scalable production systems. In this session, we’ll explore how knowledge graphs, powered by Neo4j, can provide the structure, context, and traceability GenAI systems need to perform effectively in real-world environments.
Join us to discuss:

• Common challenges in scaling GenAI projects
• How knowledge graphs ground and enhance GenAI models
• Architectures for GenAI platforms that go beyond prototypes
• Real-world lessons from deploying graph-based AI systems

Whether you're building RAG pipelines, structured agents, or domain-specific copilots, this is your chance to learn, share, and connect with others tackling the same journey—from PoC to production.

Speakers:
Prashun Javeri CTO, Monkeypatched -

While building GenAI prototypes can be fast and exciting, turning them into reliable, scalable platforms is a whole different challenge. Moving beyond demos requires thoughtful architecture—covering everything from data pipelines and knowledge grounding to feedback loops, observability, and deployment at scale.
In this talk, I’ll dive into the core architectural patterns behind production-ready GenAI platforms:

• How to integrate knowledge graphs for contextual intelligence
• Designing modular, scalable pipelines for retrieval-augmented generation (RAG)
• Managing state, versioning, and prompt orchestration
• Infrastructure choices for real-world reliability

Whether you're building internal copilots, domain-specific agents, or GenAI SaaS tools, this session will help you design systems that don’t just work in a demo—but in the wild.

Other Speakers:

TBD

Thanks to our venue partner: IDfy and our ecosystem partner: Made in Mumbai for their support in this meetup.

Whether you're a developer, data scientist, or just GenAI-curious, come see what connected intelligence really looks like in action.