Self-Correcting ML + Multimodal Search with Elastic

Elastic’s Washington user community hosts two implementation-focused talks. The first examines an ML pipeline that uses observability logs, metrics and traces to detect drift or errors and trigger corrective action. The second demonstrates multimodal search over artwork and video, using text and image inputs alongside an agent that narrows results.

Doors open at 5:30 pm with food, followed by the ML observability talk at 6:00 and the multimodal-search talk at 6:40. The event ends with networking. It is a strong fit for engineers building search, retrieval, machine-learning operations or agent-assisted discovery systems.