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# Tomb rAIder: AI Search with Kotlin


- **Event:** World Congress 2026 Europe - Virtual Stage

## Recording

[Watch recording](https://www.wearedevelopers.com/videos/1989-tomb-raider-ai-search-with-kotlin)

## Description

Most teams build AI search one of two ways: embed everything and run vector similarity, or hand the whole query to an LLM. Both hit limits — embeddings can't enforce hard requirements, and a single large prompt is slow, brittle, and hard to test.

This talk shows a more deliberate approach. Building a real search engine in Kotlin — running fully locally with Spring AI, Postgres + pgvector, and LM Studio. I show how to decompose a query and route each part to the tool that's actually best for it.
 

## Speaker

### [Dmytro Kurets](https://www.wearedevelopers.com/@dmytro-kurets)

Software Engineering Team Lead at trivago


## Related talks at this congress

- [Building an AI-Ready Content Lake: Scaling RAG and Document AI Beyond Demos](https://www.wearedevelopers.com/events/world-congress-2026-europe-virtual-stage/sessions/1506-building-an-ai-ready) — Angel Borroy
- [Solving AI Amnesia: Building "Infinite Memory" for Agents without the RAM](https://www.wearedevelopers.com/events/world-congress-2026-europe-virtual-stage/sessions/1602-solving-ai-amnesia) — Tara Khani
- [Building Agentic Applications: A Deep Dive into Zooka, an AI Cardiologist Assistant](https://www.wearedevelopers.com/events/world-congress-2026-europe-virtual-stage/sessions/1505-building-agentic) — Ahmad Adel
- [Using AI Without Losing Your Skills](https://www.wearedevelopers.com/events/world-congress-2026-europe-virtual-stage/sessions/1632-using-ai-without) — Jen Callou