Rapid AI Transformation
Agents in production, not in a sandbox.
Clouds configured around the work your team does, agents tested against your real records, and integrations that survive contact with the rest of your stack.
What it is
Implementations get slow in predictable places.
Requirements that shift between workshops. An integration nobody scoped. A UAT phase that discovers everything late, when changing it is most expensive. None of these are platform problems, which is why buying more platform never fixes them.
We run implementations the way we run every build: agents doing the reading and the first draft, senior engineers on the design and the judgment. Agent behavior gets tested like code: every conversation regression-tested against your historical records before go-live. Your admins get a system documented well enough to change without a change request to us.
What happens
Three things, in this order.
Configure against the workflow
Objects, flows and permissions follow the work your team does, not a reference architecture.
Ship agents that get tested
Agent conversations are regression-tested on your real records, and escalation to a human is designed in rather than added later.
Integrate and hand over
The systems around it - billing, telephony, the warehouse - wired up, documented, and yours to maintain.
Proof
Shipped, measured, in production.
Also in Rapid AI Transformation
Accelerated AI-readiness Assessment
AI-powered requirements gathering and specification
Rapid Legacy Migration
AI-assisted modernization and migration of legacy systems
AI-ready Platform Rebuild
Move off aging platforms onto a modern stack — agents map the old system, port the logic, and prove parity
Get started
What is stuck in your CRM roadmap?
Bring the backlog you haven't been able to get through, and we'll come back with an order to clear it in.