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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

By partnering with Nexla, we remove friction between enterprise data and production AI search, helping teams deploy scalable, real-time retrieval and RAG systems faster”

— Jon Bratseth

TRONDHEIM, NORWAY, February 18, 2026 /EINPresswire.com/ — Vespa.ai, the creator of the leading AI search platform for large-scale, real-time applications, and Nexla, the leading AI-powered data integration platform for agents, today announced a strategic partnership to address a key bottleneck in AI application development: moving production-ready data into scalable, high-performance AI search and retrieval systems.

With over 500 connectors, Nexla addresses this challenge by turning data variety from any enterprise system (structured/unstructured, batch/streaming, internal/external, modern/legacy) into ready-to-use 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.

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.
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 allow teams to migrate from other vector databases, sync operational databases into Vespa, or continuously update Vespa indexes using batch, streaming, or CDC pipelines 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.

Saket Saurabh, CEO & Co-Founder, Nexla.com: “Data integration and intelligent retrieval are two sides of the same coin in modern AI architectures. Nexla unlocks data variety, transforms and delivers enterprise grade ready-to-use data; Vespa.AI makes it 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.”

Jon Bratseth, CEO, Vespa.ai: “Vespa is built for teams that need precision, performance, and real-time execution at scale. By partnering with Nexla, we’re simplifying large-scale deployment by removing friction between data preparation and production AI search, while reducing time-to-value. Together, we’re helping teams move from raw enterprise data to production-grade AI search and RAG systems faster and with far more control.”

For more information: https://blog.vespa.ai/vespa-nexla-partnership/

About Nexla
Nexla is an enterprise-grade, AI-powered data integration platform for agents that unlocks data from any data source into production-ready data products for AI and agents. With support for 500+ connectors and multiple integration styles, including ELT, ETL, streaming, APIs, and agentic RAG, Nexla enables teams to build and manage data flows without writing code. Nexla processes over one trillion records per month for leading companies across industries.

About Vespa
Vespa.ai is an AI search platform used by companies such as Spotify, Yahoo, and Perplexity to power large-scale, real-time search, recommendation, and retrieval-augmented generation applications. The platform combines vector search, keyword retrieval, structured filtering, and machine-learned ranking in a single distributed system designed for high-throughput, low-latency workloads. Vespa is available as open source and as a managed cloud service.

Timothy Young
Vespa
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