Chapter 01
Research agenda
Applied AI studies what fails after the pilot: label drift, ownership ambiguity, alert fatigue, and ROI measurement. Methods include domain adaptation, active learning in production, and human-AI teaming designs.
Laboratory
Applied AI Lab
Enterprise deployment of research systems.
Field
First
Cross-industry
Patterns
Feedback
To research
Chapter 02
Instruments
Sandbox tenants, anonymized enterprise corpora under strict contracts, and shared evaluation definitions with product teams. The lab sits between customers and the other five laboratories.
Chapter 03
Closing the loop
Every deployment produces structured feedback — failure modes, data gaps, UX friction — that becomes backlog for Vision, AI Systems, Security, and Robotics. Applied AI exists so research compounds against real constraints.
Shared instrument set
Six laboratories. One research fabric.
Applied AI Lab shares compute, evaluation, and publication tooling with every other Zansoc lab — so discoveries compound across the stack.
Visit all labs