Nexla has introduced Express, a conversational data engineering platform designed to simplify the creation of production-grade data pipelines. This tool allows development teams to integrate diverse data sources through natural language, accelerating AI adoption by providing rich, contextual data for AI-driven applications.
- Natural language commands build secure, scalable data pipelines
- Platform supports over 550 connectors and trillions of processed records
- Enhances AI agent outputs with accurate, contextual data
What happened
Nexla introduced their Express conversational data engineering platform in November 2025, designed to overcome challenges in integrating complex enterprise data for AI use cases. Express allows development teams to describe data needs through natural language, enabling automatic creation of secure, production-grade data pipelines without coding.
The platform is now available on AWS Marketplace, providing enterprises quick access to build customized data connections. It leverages Nexla's extensive network of over 550 bidirectional connectors, enabling seamless data flow from real-time systems, data warehouses, and documents into AI applications.
Why it matters
Integrating diverse data sources to create rich contextual information is a critical bottleneck in enterprise AI adoption. Nexla's Express addresses this by enabling AI agents to access live, permission-aware data, which enhances the agents' ability to perform autonomous tasks reliably and at scale.
The platform processes over 10 trillion records annually for customers such as DoorDash, LinkedIn, Johnson & Johnson, and American Express. By delivering accurate and traceable context, it helps reduce AI hallucinations caused by stale or incorrect data, significantly improving AI output quality and enterprise trust in AI systems.
What to watch next
As more organizations seek to embed AI agents into day-to-day operations, the adoption of conversational data integration platforms like Nexla's Express will be a key enabler. Monitoring how enterprises incorporate such tools across teams—HR, procurement, finance—will demonstrate AI's expanding operational impact.
Further developments from Nexla could include expanding its connector ecosystem and refining agentic probes that dynamically discover relevant data products. This evolution will be crucial to maintaining up-to-date, permission-compliant data flows that sustain the growing complexity and scale of AI workloads in enterprise environments.