Behind every lagging transformation initiative is a set of recurring issues—many of which trace back to the same root causes. In our recent webinar, Matt Lauer, Sales Engineer at Adaptigent unpacked four of the most entrenched technical problems facing mid- to large-size enterprises. Below, we explore each one in greater detail—along with how modern integration platforms are helping companies reverse course.
1. System Complexity Isn’t Just Technical
—It’s Architectural Debt
Most enterprise IT ecosystems are inherited, not built. Years of layering new technologies on top of old ones—through M&A activity, vendor changes, and internal quick fixes—have resulted in fragmented architectures. This isn’t just inconvenient; it introduces dependency chains that make even simple updates risky and expensive.
At Adaptigent, we’ve worked with organizations where core systems were siloed to the point that mission-critical data sat inaccessible on mainframes, disconnected from digital channels. The issue isn’t the technology’s age—it’s the lack of connective tissue that can bridge those systems to modern applications without rewriting everything from scratch.
2. Adaptability Fails When Every Integration
Is a One-Off
It’s common to see one-time integrations built for specific use cases—like exposing a mainframe endpoint to serve a new channel. The problem is that these point solutions rarely scale. Once the business needs change (and they will), the team is back to square one, reengineering another brittle workaround.
One example Matt shared: a major European bank needed to connect their internal systems with World-Check for compliance screening. Using Adaptigent, they delivered both outbound API calls and inbound mainframe updates within two months. This approach is paying long term dividends as they didn’t go through a one-time connector, but via reusable integration logic that could be scaled across future initiatives.
3. Usable Data Isn’t Just Available
—It’s Context-Aware and Accessible
Enterprises often have the data—they just can’t get to it in a meaningful way. That’s especially true when data lives in transactional systems that weren’t designed to serve insights in real time. Without proper formatting, context tagging, and structured access methods, that data remains untapped.
Our platform abstracts these underlying systems so teams can work with normalized, business-ready data across interfaces. This not only powers decision-making but also enables personalization, audit trails, and data lineage—capabilities that are nearly impossible to achieve without a common integration layer.
4. Real-Time Operations Are Impossible
on a Batch-Only Mindset
Batch processing still powers many core systems, but it introduces delays that modern workflows can’t afford. Whether it’s a payment update, inventory change, or risk trigger, waiting for the next scheduled job isn’t good enough.
Where processes cannot be converted to transactional systems, caching, pre-processing, and near-real-time triggers can close the gap. Adaptigent enables teams to simulate real-time responsiveness—even when the underlying infrastructure is batch-driven—by injecting intelligence at the integration layer.
What It Takes to Move Forward
These four issues don’t resolve themselves with more investment in SaaS tools or incremental process change. They require a new way of thinking about integration—not as a bridge between old and new, but as a fabric that lets both move in lockstep.
Watch the full segment here
[/video