Vespa.ai

🤩 We’re proud to highlight Radu Gheorghe, Software Engineer at Vespa.ai, who recently delivered an insightful and impactful talk at Big Data Week! It’s incredibly inspiring to see our engineers leading the way, sharing their expertise, and driving innovation in search technology. 🚀 Stay tuned — more exciting events coming soon!

Flashback Friday: Building, learning, and innovating at Stanford TreeHacks and AICamp San Francisco! 🤖 From visual retrieval in RAG to AI-powered frameworks to test front-end, we had the chance to collaborate with some brilliant minds, push the boundaries of AI, and build innovative projects in a fast-paced, high-energy environment. 🚀 We are always grateful for the connections made and the inspiration gained. Can't wait for more opportunities to innovate and create! Andreas Eriksen Leandro Alves Theodor Kvalsvik Lauritzen Magnus E.

What if search wasn’t just about finding—but truly understanding? Vespa.ai goes beyond traditional search. It’s an AI-native application engine for building real-time, scalable, and intelligent applications. From recommender systems to personalized search, chatbots, and RAG pipelines, Vespa delivers blazing-fast, context-aware results at scale. 🚀 Watch this short explainer video to discover how Vespa can power your AI-driven applications. #SearchEngine #VectorSearch #RAG #GenAI #MachineLearning

🔙✨ #FlashbackFriday: The Future of RAG & Document Search ✨🔙 Last month, Thomas Hjelde Thoresen joined Ravit Jain on The Ravit Show to dive into the exciting advancements in Retrieval-Augmented Generation (RAG)—particularly Visual RAG—and its impact on document search. This conversation made it clear: Visual RAG is redefining how we retrieve and interact with information. Excited to see where this technology takes us next! 👉 What are your thoughts on the future of RAG and document search? #AI #RetrievalAugmentedGeneration #VespaAI #TheRavitShow #Search #informationretrieval #MachineLearning https://lnkd.in/ey55FT4w

New tutorials on using #Logstash to Vespa.ai input and output plugins: 1) Write data from (sometimes dirty) CSV files, like most of the open datasets 2) Sync with #PostgreSQL or other DBs 3) Consume from #ApacheKafka 4) Migrate from another Vespa cluster 5) Migrate data from #Elasticsearch https://lnkd.in/d5RDpFK3 As always, any feedback will be appreciated 😊

VLMs will transform how we find and interact with multi-modal data, just as LLMs transformed how we talk to applications. Join us at AICamp in San Francisco on February 13th as Andreas Eriksen walks through the steps of building an end-to-end Visual RAG application over PDFs using Vespa.ai. All code is open source, you can easily replicate this yourself with your own data! 👉 Register here: https://lnkd.in/gAZd32fT

👀 Stay ahead in RAG innovation and see how ColPali integrates visual data from PDFs in this webinar featuring Aakarsh Ramchandani, Chief Strategy Officer at RavenPack, and Jon Bratseth, CEO of Vespa.ai 👉 On-demand here: https://lnkd.in/gdBmk-eW

Nice update from Vinted Engineering on how they are progressing with their billion-scale search system. https://lnkd.in/gK69HKVa #VectorSearch #Recommendation

We thought the GigaOm Sonar Report For Vector Databases 2.0 provides a useful guide to aid decision-makers in navigating the diverse landscape of available vector databases and have made this report available as a free download: https://lnkd.in/gWY_uAX8. #VectorSearch #Vector #VectorDatabase #RAG

We're passionate about helping engineering teams build the best solutions. 🚀 We recently had the pleasure of hosting datacraft Paris, where Radu Gheorghe gave participants tools for working on various use cases from #ecommerce #search to #recommendations and #rag