Your AI systems are brittle because they were built fast.
Fast prototypes become slow to change. Systems get duplicated instead of shared, which makes them hard to maintain. Prompts and models pile up with no one tracking them, driving up cost without anyone seeing why. You pay for it in every feature request and every incident.
Migrated with the tools you already run.
The same containers, infrastructure-as-code, and languages your engineering org already uses, consolidated instead of duplicated per team.
Recognize the symptoms
The symptoms that show up first.
You can't prioritize a fix for debt you haven't inventoried.
- Every team built its own agent or its own way of pulling in company data, and nobody can say which one is the source of truth
- Dozens of prompts live in notebooks and chat logs with no versioning and no record of what's deployed
- When something breaks, nobody knows who owns it or who to call
- Credentials are sitting in code, logs, or environment variables because nobody scoped a secrets story
The systems you built to prove an idea are now the systems you have to live with.
- Every fast prototype that stays in production becomes a liability: hardcoded values, no error handling, no monitoring.
- Every team builds its own agent, its own way of pulling in company data, or trains its own custom model, so knowledge stays stuck in people's heads instead of written down.
- Prompts live across notebooks, chat logs, and ad-hoc scripts with no versioning and no clarity on what's actually deployed.
- Teams that skip a real inventory usually find more duplicated systems and undocumented dependencies than they expected.
Eight dimensions where debt lives
We don't just assess. We architect the path and execute the migration.
Five steps, run in order.
Inventory
Catalog every AI system, model, prompt, and agent that's actually running, not what the org chart says should exist.
Map dependencies
Where systems overlap, where they connect, and the hidden dependencies nobody wrote down.
Design the target state
One shared setup instead of many separate ones, so testing, monitoring, and oversight work the same way across every system.
Migrate in phases
One system at a time, tested on its own, while production keeps running, so nothing breaks along the way.
Establish ownership
Clear playbooks and a named owner for the new setup, so debt doesn't quietly build up again.
From our experts.
Writing on why AI pilots stall and the manual-work cost of not fixing it.
The same nine-phase lifecycle, applied to remediation.
Discovery through knowledge transfer, with production staying up through every phase.
Common questions.
Technical debt grows every day it's not addressed.
An assessment shows you exactly what you have, where the biggest costs are, and what remediation looks like. You'll know the real price of delay.
NDA available on request · Scoped engagements · No surprise fees