Description

Vespa is an AI Search Platform for developing and operating large-scale applications that combine big data, vector search, machine-learned ranking, and real-time inference.

It is positioned for fast, accurate, and large-scale RAG, personalization, recommendation, and search across vector, text, and structured data.

How we innovate

Vespa stands out for combining native tensor support, distributed machine-learned ranking, and vector, text, and structured search in a single platform built for large-scale, low-latency AI applications.

Use Case / Scenario

1. Search

Build search applications that combine text, vector search, and machine-learned ranking at scale.

2. Generative AI (RAG)

Use Vespa to surface relevant data for retrieval-augmented generation and other generative AI applications.

3. Recommendation and personalization

Support recommendation, personalization, and ad targeting with retrieval and model evaluation in real time.

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