Token Efficiency & Air-Gapped MLOps

All right!!!

Meetup #36: "Token effciency & Air-gapped MLOps" with Cloudera, Qdrant, evroc and SAAB will take place June 3 at AI Sweden. The program is now final! :-)

Event Program
- Doors open at 17:00 CET
- Talks begin at 17:45 CET
- There will be pizzas & drinks
- There may be a moderated Q&A session....

Speaker Line-Up
- Ewa Szyszka, DevRel Engineer at **Qdrant **will give a talk titled "Grow the Data, Shrink the Bill". Abstract: Agent efficiency through vector search. The core argument: AI agents waste tokens in four ways: context accumulation (stale tools, redundant reads), payload inefficiency (loading too much context), generative waste (restating, re-planning), and failure recovery (bad tool calls, self-correction loops). Stuffing the context window with everything works but is 50–100× more expensive than targeted retrieval. The alternative: use vector embeddings to increase information density, so an orchestrator works only with retrieved context from a vector store. You back this up with a benchmark experiment across three datasets (SWE-Bench, LongMemEval, FinanceBench) comparing agentic grep, Qdrant BM25 sparse, and Qdrant dense retrieval, measuring tokens-to-resolution as the primary metric.

- Markus Kjellner, Regional Vice President, Nordics & Baltics at Cloudera will give a talk titled "GenAI and MLOps without compromising on data sovereignty in strict air-gapped security environments". Abstract: Unlock the power of GenAI and MLOps without compromising on data sovereignty or strict air-gapped security. Discover how you can bring cutting-edge, cloud-nati