Your most valuable data doesn't live in a shiny new data lake. It lives in the ERP system that's been running for 15 years, the custom database your operations team built a decade ago, and the spreadsheets that somehow became mission-critical. The question isn't whether to replace these systems — it's how to make AI work with them.
The Replacement Myth
There's a common assumption in AI consulting: before you can do anything intelligent, you need to modernize your entire data infrastructure. Migrate to the cloud, consolidate into a data warehouse, standardize all your schemas, and then — maybe — you can start thinking about AI.
This approach is expensive, slow, and usually unnecessary. Worse, it delays the value that AI can deliver by months or years. By the time the infrastructure modernization is done, the business has moved on.
The Bridge Approach
At CE Inc, we take a different approach. Instead of replacing your existing systems, we build bridges between them and modern AI capabilities. These bridges are:
- Lightweight. We use APIs, data connectors, and middleware that sit alongside your existing systems without modifying them.
- Secure. Data stays where it is. We bring the AI to the data, not the other way around. Access controls and encryption are built in from the start.
- Incremental. You start getting value immediately, with one integration at a time. No big-bang migration required.
- Reversible. If something doesn't work, you can remove the bridge without affecting the underlying system.
Common Integration Patterns
Over dozens of projects, we've identified several patterns that work reliably across different legacy environments:
Read-Only Data Access
The simplest pattern. We create a read-only connection to your legacy database, transform the data into a format the AI model can consume, and deliver insights without ever writing back to the source system. This is ideal for analytics, reporting, and decision support.
Event-Driven Integration
For systems that need real-time awareness, we set up event listeners that detect changes in your legacy systems and trigger AI workflows automatically. A new order comes in, a support ticket is filed, a sensor reading exceeds a threshold — the AI responds in seconds.
API Wrapping
Many legacy systems have no API at all. We build thin API layers around them, exposing the functionality that AI needs while keeping the underlying system untouched. This is the most common pattern for systems that were built before APIs were standard practice.
Getting Started
The first step is always an assessment: understanding what systems you have, what data they contain, and what AI use cases would deliver the most value. From there, we design the integration architecture and start building — usually with the highest-value, lowest-risk connection first.
If you're sitting on years of valuable data locked in legacy systems and want to explore what AI can do with it, let's have a conversation.