Vectorize Your Open Source Search Engine
06-19, 10:40–11:00 (Europe/Berlin), Kesselhaus

Fascinated by vector search but don't know where to start?
Join us to crack the code and leverage the potential of vector search to delight your users.

Neural search (a.k.a. Vector search) has rewritten the standards of information retrieval in many different domains.
Vector search can help you gather a better understanding of the user query intent, drive product recommendations, search across different source data (text, images, audio, video), deliver better results, improve personalization and create a more successful user experience. Vector search goes beyond keywords to harvest the potential of graphs and embeddings to match users to the intended document, product, job, picture, song, or video.
As fascinating as this may sound it's easy to find ourselves lost in the deluge of new information.
If you're struggling to get started, understand what vector search can bring to the party, add cool new models such as OpenAI models and want to avoid common pitfalls, this talk is for you.

See also: Slides (5.3 MB)

Atita has been working to develop, customize, and optimize Enterprise & E-commerce search engines for many years. She is an active contributor to many open-source tools. She holds 2 Masters degrees in Computer Applications and Strategic Business Management. She has worked and supported in many different roles in various organizations and even founded a small Search consultancy in India in 2017.
She has a keen interest in personalizing search and influencing customer interaction using NLP, ML, and AI.