Artwork

Qdrant 2025 Conference Interviews

DataTalks.Club

25 subscribers

published

iconShare
 
Manage episode 521641186 series 2831626
Content provided by DataTalks.Club. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by DataTalks.Club or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

At Qdrant Conference, builders, researchers, and industry practitioners shared how vector search, retrieval infrastructure, and LLM-driven workflows are evolving across developer tooling, AI platforms, analytics teams, and modern search research.

Andrey Vasnetsov (Qdrant) explained how Qdrant was born from the need to combine database-style querying with vector similarity search—something he first built during the COVID lockdowns. He highlighted how vector search has shifted from an ML specialty to a standard developer tool and why hosting an in-person conference matters for gathering honest, real-time feedback from the growing community.

Slava Dubrov (HubSpot) described how his team uses Qdrant to power AI Signals, a platform for embeddings, similarity search, and contextual recommendations that support HubSpot’s AI agents. He shared practical use cases like look-alike company search, reflected on evaluating agentic frameworks, and offered career advice for engineers moving toward technical leadership.

Marina Ariamnova (SumUp) presented her internally built LLM analytics assistant that turns natural-language questions into SQL, executes queries, and returns clean summaries—cutting request times from days to minutes. She discussed balancing analytics and engineering work, learning through real projects, and how LLM tools help analysts scale routine workflows without replacing human expertise.

Evgeniya (Jenny) Sukhodolskaya (Qdrant) discussed the multi-disciplinary nature of DevRel and her focus on retrieval research. She shared her work on sparse neural retrieval, relevance feedback, and hybrid search models that blend lexical precision with semantic understanding—contributing methods like Mini-COIL and shaping Qdrant’s search quality roadmap through end-to-end experimentation and community education.

Speakers

Andrey Vasnetsov

Co-founder & CTO of Qdrant, leading the engineering and platform vision behind a developer-focused vector database and vector-native infrastructure.

Connect: https://www.linkedin.com/in/andrey-vasnetsov-75268897/

Slava Dubrov

Technical Lead at HubSpot working on AI Signals—embedding models, similarity search, and context systems for AI agents.

Connect: https://www.linkedin.com/in/slavadubrov/

Marina Ariamnova

Data Lead at SumUp, managing analytics and financial data workflows while prototyping LLM tools that automate routine analysis.

Connect: https://www.linkedin.com/in/marina-ariamnova/

Evgeniya (Jenny) Sukhodolskaya

Developer Relations Engineer at Qdrant specializing in retrieval research, sparse neural methods, and educational ML content.

Connect: https://www.linkedin.com/in/evgeniya-sukhodolskaya/

  continue reading

201 episodes