RushDB in Action: Building AI-Native Apps with Self-Aware Graphs

Modern data is inherently complex, deeply interconnected, and constantly evolving—yet most application stacks are still built on infrastructure designed for flat, isolated records. Historically, developers have lacked reliable, scalable tools to work with nested, relational, and emergent data structures in real time. In the era of AI agents and adaptive interfaces, the ability to process and reason over graph-shaped data at the speed of creation is becoming critical to ensure smooth, intelligent experiences.

In this session, Artemiy Vereshinskiy creator of RushDB, will introduce a graph-native, zero-configuration database designed to meet these challenges. RushDB aims to eliminate the need for rigid schemas, manual (de)normalization, and fragile aggregation logic, allowing developers to ingest and query complex data as-is, while the graph does the heavy lifting.

You will learn how graph thinking simplifies full-stack development, explore the architecture and design of RushDB, and see how self-aware graph storage enables smarter, context-aware applications. This session will demonstrate how a single graph can serve as the source of truth across front-end, back-end, and ML pipelines—unlocking rapid iteration and AI-native performance without traditional data modeling overhead.

By the end of the talk, you will understand how graph-native infrastructure can help you reduce developer complexity, accelerate product velocity, and build adaptive systems that match the structure and speed of real-world data.

Speaker: Artemiy Vereshchinskiy

Resources:
Get Started with Aura – https://bit.ly/3LOLrjh
Deployment Center – https://bit.ly/4jOelM3
Ground AI Systems and Agents with Neo4j – https://bit.ly/4oVsnyb

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