Most enterprises are assembling AI capabilities the way they've always bought software: one tool at a time, from different vendors, solving different problems.
The result is a stack that looks reasonable on a slide and falls apart in production.
The Procurement Trap
Procuring multiple AI solutions is slow, expensive, and politically exhausting.
Each vendor requires a separate security review. Separate legal negotiation. Separate IT onboarding. Separate executive sponsor to justify the spend. By the time you've signed three vendors, you've spent 6-9 months in procurement—and you haven't deployed anything yet.
Then comes the integration work. These systems weren't designed to work together. The APIs don't align. The data models conflict. The authentication flows don't match. You end up building custom middleware that no one budgeted for, no one wants to maintain, and no one fully understands six months later.
One Fortune 500 retailer we work with calculated that their integration costs across AI vendors exceeded the combined subscription fees in year one. They were paying more for glue than for capability.
The System of Record Problem
When data lives in Vendor A's cloud, analytics run in Vendor B's platform, and agents execute in Vendor C's infrastructure—where is the system of record?
This isn't a theoretical question. It creates real operational chaos:
- Edits made in one system have to be pushed back to another. Which version is authoritative?
- Data pipelines shuttle information between clouds, each hop introducing latency, cost, and risk.
- When something goes wrong, debugging requires traversing three vendor support queues who each blame the others.
A global CPG company we deployed with had exactly this challenge: forecasting data in one system, planning tools in another, execution in a third. Their analysts spent more time reconciling sources than actually analyzing.
The fundamental issue: when you fragment AI across vendors, you fragment truth. And fragmented truth is expensive to maintain.
The Integration Tax
Every point of integration is a point of failure, a security surface, and a governance gap.
The integration tax isn't just the upfront engineering cost—it's the ongoing maintenance burden. Every time a vendor updates their API (on their schedule, not yours), your integrations break. Every time you need to add a new capability, you're negotiating with the existing spaghetti.
This tax compounds over time. Year one, it's manageable. Year three, it's a significant drag on velocity. Year five, it's technical debt that constrains every strategic decision.
The Simpler Path
There's an alternative: a unified platform that handles governance, data management, and agent orchestration in one layer.
This doesn't mean sacrificing flexibility. The right architecture is batteries-included but configurable—it comes with the services you need out of the box, but lets you swap in existing infrastructure where you've already invested.
The integration tax disappears when there's nothing to integrate. One permissioning model. One system of record. One place where your AI capabilities live.