Vespa

Ever wondered how the world's leading companies handle billions of data items and thousands of queries per second with AI?

RecommendedVespa.ai is a powerful, enterprise-grade AI search platform offering unparalleled performance and flexibility for complex, data-driven AI applications.

Vespa.ai is an AI Search Platform designed for developing and operating large-scale applications that integrate big data, vector search, machine-learned ranking, and real-time inference. It offers native tensor support for complex ranking and decisioning, enabling real-time AI applications like RAG, recommendation, and intelligent search at enterprise scale.

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Key Features:
  • Vector, text, and structured search
  • Distributed machine-learned ranking
  • Unbeatable performance (sub-100ms latency)
  • Infinite automated scalability
  • Continuous deployment & upgrades
Pros
  • Enterprises building large-scale AI search platforms
  • Developers creating real-time recommendation systems
  • Organizations implementing advanced GenAI (RAG) applications
Cons
  • Requires significant technical expertise for implementation and optimization
  • Pricing details are not transparently listed, suggesting enterprise-focused custom quotes
  • Steep learning curve due to its comprehensive feature set and complexity
Pricing
enterpriseFree tier
Trial:Free trial available
Categories:
AI InfrastructureSearch & KnowledgeData & Analytics
Tags:
vector databaseAI searchmachine learningreal-time inferenceRAGrecommendationscalabilityopen source
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Quick Decision
Try if: You should try Vespa.ai if you are an enterprise or a developer working on large-scale, real-time AI applications that require advanced search, recommendation, or RAG capabilities with high performance and scalability.
Skip if: Skip if you are looking for a simple, plug-and-play search solution for small to medium-sized data sets, or if you lack the technical resources for complex platform implementation and management.
Not for: Small businesses with basic search needs; Users seeking a simple, off-the-shelf search solution without custom development
Trust Signals

  • Founded

    2000

  • Team Size

    medium
Notable Customers
SpotifyElicitYahooFarfetchPerplexity
Tech Details
Platforms
webapicloud
Integrations
AWSTensorFlowONNXXGBoostLightGBM
Open Source
Yes
Support
Channels
documentationsupport portal (paid plans)email (free support)Slackdeveloper center
Company

  • Name

    Vespa.ai AS

  • Location

    Trondheim, Norway (Headquarters)

Vespa.ai started as a web search innovator in the early 2000s and now delivers a platform powering various AI and data use cases globally. Their culture emphasizes collaboration, long-term vision, and technical excellence.

FAQ

What is Vespa.ai?

Vespa.ai 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's designed for real-time AI applications like RAG, recommendation, and intelligent search.

Does Vespa.ai offer a free trial?

Yes, Vespa.ai offers a free trial. You can start your free trial directly from their website.

What kind of search capabilities does Vespa.ai provide?

Vespa.ai provides industry-leading vector search, text search, and selection in structured data. This includes support for multiple vector fields, tensor values, true positional text indexes with linguistics integration, and structured data operators.

How does Vespa.ai handle machine-learned ranking?

Vespa.ai can generate a wide selection of ranking signals from query matching and data fields. These signals can be combined using mathematical functions over tensors, including machine-learned models in formats like ONNX or XGBoost. It supports multi-phase ranking for optimized inference.

What industries can benefit from Vespa.ai?

Vespa.ai is used across various industries including AdTech, Digital Commerce, FinTech, Health & Life Sciences, Market Intelligence & Data Providers, and Travel and Hospitality.

Use Cases
  • Enterprises building large-scale AI search platforms
  • Developers creating real-time recommendation systems
  • Organizations implementing advanced GenAI (RAG) applications
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