Nexla and Vespa.ai Partner to Simplify Real-Time AI Search Across Hundreds of Enterprise Data Sources

Native integrations reduce setup time and ongoing maintenance by making it easy to ingest, index, and continuously update data from enterprise systems

Nexla, the enterprise-grade AI-powered data integration platform for agents, announced a strategic partnership with Vespa.ai, the creator of the leading AI search platform for building and deploying large-scale, real-time AI applications. The partnership eliminates one of the biggest bottlenecks in AI application development: getting production-ready data into scalable, high-performance AI search and retrieval systems.

Organizations building AI-powered applications face a critical challenge: connecting and preparing enterprise data from hundreds of disparate sources before it can power intelligent search and retrieval. This data variety – structured/unstructured, batch/ streaming, modern/ legacy, creates complexity that slows AI deployment to production.

With over 500 pre-built connectors, Nexla addresses this challenge by transforming data variety from any enterprise system into production-ready data products for AI and agents, while Vespa provides the distributed search, vector retrieval, and real-time inference capabilities required to serve AI-powered applications at scale. Together, they create a seamless path from raw enterprise data to intelligent, production-grade AI search.

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As part of the partnership, Nexla launched native Vespa integrations that make working with Vespa faster and simpler:

• Vespa Connector in Nexla: Seamlessly pipes data from sources such as Amazon S3, PostgreSQL, Snowflake, APIs, and even existing vector databases directly into Vespa, without custom code or complex configurations.
• Vespa Nexla Plugin CLI: Automatically generates draft Vespa application packages, including schema files, directly from Nexla’s metadata-defined data products (Nexsets), dramatically reducing setup time and configuration errors.

These capabilities enable teams to migrate from other vector databases, sync operational databases into Vespa, or continuously update Vespa indexes using batch, streaming, or CDC pipelines, all without writing code.

The combined solution is especially valuable for organizations building or scaling:

• AI search and RAG applications requiring hybrid retrieval across vectors, keywords, and structured filters
• High-throughput, low-latency systems serving billions of documents with real-time updates
• Complex ranking and inference pipelines, including multi-phase ranking and LLM integration

Nexla prepares and governs the data; Vespa executes advanced retrieval, ranking, and inference where the data lives.

“Data integration and intelligent retrieval are two sides of the same coin in modern AI architectures,” said Saket Saurabh, CEO and Co-Founder of Nexla. “Nexla unlocks data variety, transforms it, and delivers enterprise-grade, ready-to-use data products; Vespa.ai makes that data searchable and actionable in real time. This partnership creates a powerful combination for organizations building agentic RAG, recommendation systems, and AI-powered search at scale. Together, we’re removing the friction between data preparation and intelligent retrieval, so teams can focus on building transformative AI experiences instead of wrestling with data plumbing.”

“Vespa is built for teams that need precision, performance, and real-time control at scale,” said Jon Bratseth, CEO of Vespa.ai. “By partnering with Nexla, we’re removing friction between data preparation and real-time execution, so teams can move from raw enterprise data to production-grade AI search and RAG systems faster and with far more control.”

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