Graph Mastery to AI: : Unleashing the Power of Connections
Graph technology has emerged as the fastest-growing sector in database systems over the past decade—and now, it's at the heart of AI transformation. This talk explores the strategic imperative of mastering graph technologies for professionals designing intelligent systems, optimizing codebases, and architecting future-ready enterprises.
Mastering graph databases, knowledge graphs, and advanced algorithms is no longer a niche skill—it's foundational to enabling AI use cases, powering semantic search, driving recommendation engines, and orchestrating Retrieval-Augmented Generation (RAG) with high precision.
In this comprehensive session, we'll explore high-level graph algorithms that form the backbone of modern, complex systems and discuss how these algorithms are integral to the architecture of efficient graph databases. We will delve into the advanced functionalities and strategic implementations of knowledge graphs, illustrating their essential role in integrating disparate data sources, empowering AI applications including generative AI, and enhancing business intelligence.
Join us to navigate the complexities and opportunities this dynamic field presents, ensuring you remain at the cutting edge of technology and continue to drive significant advancements in your projects and enterprises.
What You’ll Learn:
Advanced Graph Algorithms
Concise review of key graph theory concepts tailored for AI and data engineers.
Application of algorithms like Greedy, Dijkstra's, Bellman-Ford, and PageRank for real-world graph optimization, pathfinding, and influence modeling.
Graph Database Architecture
Comparison of graph vs. relational models for large-scale, interconnected data.
Best practices in data modeling, indexing, and query performance tuning in platforms like Neo4j, TigerGraph, and Amazon Neptune.
Mastery of Knowledge Graphs
How to build and scale enterprise-grade knowledge graphs for semantic search, personalization, and intelligent recommendations.
Role of ontologies, entities, and relationships in structuring organizational knowledge.
Graph-RAG and AI-Enhanced Use Cases
Deep dive into Graph-RAG (Graph-enhanced Retrieval-Augmented Generation): combining structured knowledge graphs with unstructured retrieval to power trustworthy, explainable generative AI.
Use cases:
Domain-specific copilots with traceable knowledge lineage.
AI assistants that reason over connected knowledge.
Compliance-aware search and recommendations.
Customer 360 + Agent 360 views for enterprise workflows.
Case Studies and Future Technologies
Real-world case studies of graph adoption in healthcare, finance, e-commerce, and public sector AI.
Preview of emerging trends:
Graph Neural Networks (GNNs)
Hybrid vector–graph databases
Multimodal reasoning over structured + unstructured data
Outcomes & Takeaways:
By the end of this session, you will:
Understand why graph mastery is foundational for AI and system innovation.
Learn to architect performant, scalable graph systems for enterprise use.
See how Graph-RAG bridges structured knowledge and LLMs to deliver smarter AI assistants.
Be equipped to apply graph technologies to drive innovation, efficiency, and AI trustworthiness in your own organization.
About Rohit Bhardwaj
Rohit Bhardwaj is a Director of Architecture working at Salesforce. Rohit has extensive experience architecting multi-tenant cloud-native solutions in Resilient Microservices Service-Oriented architectures using AWS Stack. In addition, Rohit has a proven ability in designing solutions and executing and delivering transformational programs that reduce costs and increase efficiencies.
As a trusted advisor, leader, and collaborator, Rohit applies problem resolution, analytical, and operational skills to all initiatives and develops strategic requirements and solution analysis through all stages of the project life cycle and product readiness to execution.
Rohit excels in designing scalable cloud microservice architectures using Spring Boot and Netflix OSS technologies using AWS and Google clouds. As a Security Ninja, Rohit looks for ways to resolve application security vulnerabilities using ethical hacking and threat modeling. Rohit is excited about architecting cloud technologies using Dockers, REDIS, NGINX, RightScale, RabbitMQ, Apigee, Azul Zing, Actuate BIRT reporting, Chef, Splunk, Rest-Assured, SoapUI, Dynatrace, and EnterpriseDB. In addition, Rohit has developed lambda architecture solutions using Apache Spark, Cassandra, and Camel for real-time analytics and integration projects.
Rohit has done MBA from Babson College in Corporate Entrepreneurship, Masters in Computer Science from Boston University and Harvard University. Rohit is a regular speaker at No Fluff Just Stuff, UberConf, RichWeb, GIDS, and other international conferences.
Rohit loves to connect on http://www.productivecloudinnovation.com.
http://linkedin.com/in/rohit-bhardwaj-cloud or using Twitter at rbhardwaj1.