Nexla Blog

AI Agents

Artificial Intelligence, Data Engineering, Data Integration, Data Products, GenAI

The Context Graph Paradox: When More Data Makes AI Agents Worse

Discover why context graphs fail at scale and how semantic structure delivers reliable runtime context for enterprise AI agents.

By Nexla Team

Artificial Intelligence, Data Engineering, Data Integration, Data Products, GenAI

Context Engineering: The Missing Discipline in Enterprise AI

Enterprise AI agents fail when the context behind their decisions is incomplete, stale, or conflicting. Context engineering ensures agents receive accurate, permission-aware runtime context for reliable decisions.

By Niket Sourabh

Nexla Blog: The Architecture That Converts Travel Inspiration Into Itineraries

Featured

Artificial Intelligence, Data Engineering, Data Integration, GenAI

The Architecture That Converts Travel Inspiration Into Itineraries

Explore how a multimodal AI pipeline built with NVIDIA models, Nebius infrastructure, and Nexla orchestration converts social media travel videos into structured itineraries.

By Nexla Team

Artificial Intelligence, Data Automation, Data Integration

How AI Is Transforming Data Engineering: From Code to Prompts

AI is shifting data engineering from code-heavy ETL to prompt-driven pipelines. Explore where LLMs fit, common pitfalls, and how Nexla makes AI-ready data workflows practical.

By Nexla Team

Artificial Intelligence, Data Engineering, Express, Product Updates

Generative UI – Building Delight in AI Agent UX

Explore how Express.dev makes AI agents capable of generating rich, interactive UI for structured data workflows. From XML-driven forms to real-time validation and OAuth flows, generative UI turns chat into a truly collaborative experience.