Not everything can fit in rows and columns

The Graph Database has been there from a very long time with very restricted use as it requires a lot of time and effort to get started. The way data becoming more unstructured and fitting them in rows and columns is painful, NoSQL solves some problem but it kills the valuable relationship between data.

The Dgraph is a new Graph Database minimizing the time and effort requires to get started with a Graph Database or using a Graph Database as a primary database.

This talk is to get you a heads up about Dgraph as a database, how it can help you with your unstructured data and what it takes to use it in your next project.

Building an ecosystem for Preventing Health Care in India

As of today the preventing health care in India is almost doesn't exists, the idea is to develop a product to help users store their medical history in digital format and suggest the means to prevent future health problems. The product was called Swasthex (which is shut down due to some challenges) and has two major parts one to help parents onboard their kids and others to use by Schools, Labs and Doctors to store and access the medical records.

Build a Movie Recommendation Chatbot using Neo4j and Vertex AI

Ever wondered how Netflix seems to know exactly what you want to watch? In this hands-on codelab, we’ll build a smart movie recommendation chatbot powered by Neo4j and Google’s Vertex AI. You’ll learn how to model data as a graph, use embeddings for smarter retrieval, and integrate it all into a conversational AI experience. Perfect for developers looking to bring intelligence into their apps—minus the Hollywood drama.

How to Say No to AI Hype - A Framework for Evaluating AI Initiatives Without the FOMO

"We need AI in this." - Every stakeholder, everywhere, right now.

The pressure to ship AI features is real. The fear of falling behind is real. But so is the graveyard of AI projects that cost six months, delivered nothing, and quietly got deprioritized. This session gives you the structured, defensible framework to cut through the noise and make smart bets on AI, without being the person who blocked innovation or the one who greenlit a disaster.

What's in it for you
You'll leave with a 4-axis evaluation model covering feasibility, risk, ROI, and reversibility, plus a set of red flag patterns that separate genuine AI opportunities from expensive science projects dressed up in a product roadmap. Real proposal case studies included: ones that should have been built, and ones that absolutely shouldn't have been. You'll never sit in an AI initiative kickoff the same way again.

The Architecture Patterns for AI-Integrated Systems

Your microservices are deterministic. Your AI components are not. That mismatch will bite you.

AI doesn't fail like normal software, it drifts, hallucinates, and degrades silently. This session gives architects and senior engineers the patterns they've been missing.

How to wrap non-deterministic AI components inside reliable, observable, production-grade systems.

What's in it for you
Walk away with a concrete toolkit, circuit breakers for LLM calls, fallback chains when models go sideways, contract testing strategies for AI outputs, and observability hooks that tell you when your AI is lying to your system before your users notice.

No theory. All battle-tested architecture decisions you can take back to your team next day.

The Principal Engineer's Playbook for the AI Era - What Changes, What Doesn't

AI is making junior devs faster. So what exactly is your value now?

This is the talk no one wants to admit they need. With AI compressing the skill gap and automating the work that used to signal seniority, the role of the principal engineer is quietly being redefined. This session is a candid, experience-backed conversation about navigating that shift with clarity rather than anxiety.

What's in it for you
You'll get a clear-eyed breakdown of which principal-level skills AI genuinely threatens, which ones become more valuable, and how to deliberately reposition your technical leadership for the next decade. Expect honest takes on mentorship, system thinking, architectural judgment, and the one thing AI will never replace, the ability to ask the right question in the first place.

Tracing Agent Decisions with Graph Evals and Neo4j

AI agents don’t just need to perform, they need to be understood, trusted, and improved.
Traditional evals only look at inputs and outputs, ignoring the messy middle where most agent failures happen.

This session introduces Graph Evals, a practical technique where every agent step (actions, states, tool calls, reasoning hops, failure points) is stored as a knowledge graph. By modeling an agent’s internal decision journey in Neo4j, we can analyze its reasoning patterns, detect blindspots, identify loops, and understand why it behaved the way it did.

Attendees will learn how to build a graph-based eval pipeline, visualize agent reasoning paths, run structural queries to catch failure modes, and continuously refine agent policies using graph insights.

Perfect for teams deploying production-grade agents and anyone who wants their AI to act less like a black box.

Prompt, Plan, Perform - The Agentic Revolution in AI

Curious about how AI really works under the hood? Tired of hearing buzzwords like “LLM” and “Agents” thrown around without context? This session is your no-fluff, high-energy, beginner-friendly guide to understanding the most disruptive tech of the decade, Large Language Models and AI Agents.

From prompting to planning, you’ll learn how AI agents can act, reason, and operate with goals, making them useful for tasks far beyond simple chatbot Q&A.

Key learnings
- Clearly define what a Large Language Model (LLM) is and how it works
- Understand the strengths, limitations, and ideal use cases for LLMs
- Learn what differentiates AI Agents from chatbots and traditional tools
- Walk away with a framework to evaluate and build LLM-powered solutions

Beyond Retrieval: Adding a Reasoning Layer to RAG with Neo4j

The reasoning layer in my RAG system is powered by Neo4j’s knowledge graph, which acts as a structured context source beyond flat document retrieval.

This hybrid system lets the LLM “think” in terms of relationships, not just keywords, adding explainability and depth to its answers.

Building Knowledge Base for Real Estate using Gemma and Neo4j

In this presentation, we delve into the development and deployment of a custom Large Language Model (LLM) tailored for a major infrastructure company. Leveraging the capabilities of Gemma and Neo4j, we created an advanced, queryable knowledge base that consolidates data from past real estate projects. This solution not only enhances data accessibility and retrieval but also demonstrates the transformative potential of AI in the real estate sector. Attendees will gain insights into the design, implementation, and benefits of integrating LLMs with robust database systems to streamline knowledge management and drive informed decision making.

A Deep Dive into Design System

In today's rapidly evolving tech world, designing digital products that are user-friendly, visually appealing, and scalable has become increasingly challenging. To meet these challenges, many companies are adopting design systems, a collection of reusable components, guidelines, and best practices that help create consistent and cohesive user experiences across products and platforms.

In this session, we will take a deep dive into design systems, discussing the key concepts, benefits, and challenges of adopting a design system for your organization. We will explore the different types of design systems, including style guides, component libraries, and pattern libraries, and how they can be customized to fit your specific needs.

We will also look at real-world examples of design systems from industry leaders like Google, Airbnb, and Salesforce, and examine their design principles and best practices. You will learn how to create and maintain a design system, how to ensure its adoption and success within your organization, and how to measure its impact on your design and development processes.

Whether you are a designer, developer, or product manager, this session will provide valuable insights into how design systems can improve your team's productivity, consistency, and creativity. Join us to learn from the experts and take your design skills to the next level.

A brief history of JavaScript bundlers

JavaScript bundling has been a cornerstone of web development, and over time, bundling tools have undergone significant transformations. In this talk, we'll delve into the fascinating history and evolution of JavaScript bundlers.

We'll explore the inner workings of these tools, uncovering the fundamental problems they were designed to solve. Discover how bundlers have adapted to the changing landscape of web development and how their evolution impacts developers and applications today.

Whether you're a seasoned developer interested in the history and intricacies of your favorite tools or a newcomer looking to understand the pivotal role bundlers play in modern web development, this session will provide valuable insights. Join us to gain a deeper appreciation for the evolution of JavaScript bundlers and how it shapes the way we build web applications.

A practical guide to GraphQL

Join us for an enlightening journey into the world of GraphQL as we demystify this revolutionary technology. In this engaging talk, you'll gain a deep understanding of GraphQL's power and versatility. We'll break down the complexities into practical, actionable insights, making them accessible to newcomers and experienced developers alike.

Discover how GraphQL simplifies data querying, empowers front-end developers, and streamlines your API architecture. You'll learn how to design efficient, flexible APIs and avoid common pitfalls through real-world examples and hands-on demonstrations. From building queries to optimizing performance, we'll provide a comprehensive guide for harnessing the true potential of GraphQL.

Leave this session equipped with the knowledge and tools you need to implement GraphQL in your projects, enhancing your development capabilities and setting you on the path to creating more efficient, adaptable, and responsive applications. Whether you're a developer looking to level up your skills or a tech enthusiast eager to explore the future of data querying, this practical guide is your key to unlocking the full potential of GraphQL.

Discover how GraphQL simplifies data querying, empowers front-end developers, and streamlines your API architecture. You'll learn how to design efficient, flexible APIs and avoid common pitfalls through real-world examples and hands-on demonstrations. From building queries to optimizing performance, we'll provide a comprehensive guide for harnessing the true potential of GraphQL.

Beyond Tables - Leveraging Graph Database for Modern Data Challenges

Explores the limitations of traditional relational databases in handling complex, interconnected data. The session highlights how graph databases excel in scenarios like social networks, fraud detection, recommendation systems, and supply chain management. It covers the fundamentals of graph databases, their benefits, and real-world use cases, empowering participants to solve modern data challenges with graph-powered insights.