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Important Notes: This is paid conference, Get your ticket on the event website is required for admission. Use code AICAMP for 25% off.

  • Sep 9th - Pre-event training
  • Sep 10th - Main Conference day

Join the Vespa and retrieval community in London for a full day dedicated to building better AI search and retrieval systems. Vesap ai live 2026 brings together engineers, developers, and AI practitioners to share ideas, learn from real-world deployments, and connect with others shaping the future of AI-powered search.

## What to expect

  • Practical talks from teams building AI applications in production
  • Real-world lessons on search, retrieval, ranking, and RAG
  • A lively panel discussion with industry experts
  • An interactive unconference barcamp session
  • Plenty of time for networking, conversations, and great food
  • A drinks reception after the conference ends

## Event details

Main event: September 10, 2026

## Optional pre-event training: September 9

Get hands-on with Vespa the day before the event, at the same Lumiere London Underwood venue:

  • Vespa 101: Ideal if you're getting started. Topics covered:
  • Introduction to Vespa and its APIs
  • Lexical Search
  • Vector Search
  • Hybrid Search
  • Result Grouping
  • Ranking 202: A deeper dive into improving retrieval quality. Topics covered:
  • Boosting and personalization
  • Evaluating embedders
  • Learning to rank
  • Chunking
  • Recommendations

Training spots are limited, so be sure to add this when registering if you'd like to attend. You will need a laptop with an updated browser.

## Who should attend?

  • AI and ML engineers
  • Search and relevance teams
  • Developers building RAG applications
  • Technical leaders exploring scalable AI systems

You don't have to be a Vespa customer to join. Whether you're new to Vespa or already running AI search in production, this is a great opportunity to learn from others and meet the community.

Save your spot today — we look forward to seeing you in London!

Related topics

Artificial Intelligence
Deep Learning
Machine Learning
Natural Language Processing
Data Science

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