AI adoption
Most AI pilots die in the gap between "it works" and "people use it." We put the engineers who build it and the change leaders who drive adoption on the same team, from the first workshop to the day it becomes how work gets done.
The problem
The use case was picked for the demo, not for the people who would use it every day.
The build team rolls off, the business never took ownership, and usage quietly fades.
Security, compliance, and clinical or operational review arrive after the build, not before it.
Our approach
Start from a workflow with a measurable cost, an owner, and users who want the help.
Former AWS engineers design and ship on AWS AI services.
Change leaders redesign roles and workflows, train users, and set up governance before go-live.
Track usage and outcomes after launch, and tune both the system and the process until it sticks.
Proof
Healthcare, Amazon Connect + AI
Amazon Connect with agentic AI and secure agent messaging for a new service line, replacing a legacy platform.
8 weeks to production50 agents onboarded$3M saved vs. legacy platform
AWS offers partner funding programs for qualifying proofs of concept and migrations. We know how they work, what qualifies, and how to build a plan that does. We've used them on Amazon WorkSpaces, Amazon Connect, and AWS landing zone projects, among others.