Domain-specific intelligence systems
Industry context changes what an AI system must know, what failure costs, which evidence matters, and where humans retain authority. We engineer from that reality outward.
Explore the domainsDomain truth before model choice
Domain systems / 01—06
Evidence-grounded copilots, multimodal clinical workflows, patient intelligence, and carefully bounded automation designed around consequence.
Adaptive learning models, source-grounded tutors, assessment intelligence, and institutional knowledge systems evaluated for pedagogy—not fluency alone.
Multimodal discovery, recommendation systems, merchandising copilots, service agents, and demand intelligence built around your catalogue and customers.
Guest copilots, voice and multilingual systems, property knowledge, service orchestration, and personalization with visible staff control.
Vision-enabled field systems, document intelligence, exception agents, predictive signals, and operational copilots grounded in live network data.
Private knowledge models, research agents, document intelligence, decision copilots, and evaluation workflows that compound institutional expertise.
How we enter a domain
Learn the terminology, evidence, ambiguity, and tacit knowledge experts use.
Observe the judgment, workflow, exceptions, and systems surrounding the task.
Define error cost, security, regulation, autonomy boundaries, and human authority.
Turn domain truth into datasets and rubrics that can select and improve the model.
YOUR DOMAIN IS MORE SPECIFIC THAN A FOUNDATION MODEL.