Bank tech stacks are beautiful monsters. Mainframes still process your mortgage payments. Cloud-native AI models screen for fraud. There’s an AS/400 humming in the background while Kubernetes clusters chew through credit scoring models in real time. And between the ends of the spectrum, there’s an alphabet soup of everything else – CRM, ECM, ERP, LMS, custom middleware, intranet file systems, vendor APIs, and three decades of SharePoint.
Centralization promised relief. One system to unify the chaos. One database to hold it all. It sounded elegant. Until you tried it (it didn’t work out that well for Sauron either).
It turns out pulling millions of records from high-uptime systems, reformatting them into something your analytics platform understands, and keeping it all in sync is not elegant. It’s slow. It’s fragile. It’s expensive – and it never ends. While you’re waiting for the ETL jobs to finish, your data is already out of date.
Worse, you’ve just moved critical information away from the systems that process it best. Mainframes aren’t fast because they’re modern – they’re fast because they’re optimized. Pulling that data into a cloud warehouse introduces latency, adds risk, and breaks compliance. It creates a whole new stack that now needs governance, monitoring, and another round of budget approvals.
Leave migration to the birds
SWIRL doesn’t migrate the mess. SWIRL makes sense of it.
No data movement. No reformatting. No guessing what your agents are allowed to see. SWIRL searches your systems live, in place, without breaking security protocols or rewriting your infrastructure.
Mainframe or Snowflake. Oracle or OneDrive. SharePoint, CRM, call logs, policy guides, PDF attachments – SWIRL sees all, searches all. And it does it in real time. SWIRL gives your agents exactly what they need, filtered by role, ranked by confidence, trimmed to the context of the question.
You don’t have to centralize anything. You don’t have to wait.
Compliance is more painful when the answers are buried
Compliance in banking isn’t optional. It’s existential. But chasing down documentation across systems that don’t talk to each other shouldn’t be part of the job.
You need to find out which residential mortgages were approved without a valid property on file. SWIRL searches loan origination systems, pulls approval flows, checks attached files, and flags violations. You don’t write a query. You don’t build a report. You ask. The agent finds.
Your audit team needs to prepare for an upcoming review. They don’t want a zip file of memos and folders full of approval chains. They want the story. What happened, who approved what, when, and where the gaps are. SWIRL retrieves it all, organizes it, links back to sources, and lets them drill into the risk—not the filesystem.
Training fails from inaccessibility
Your training team updates the LMS. New policy doc goes into the file share. Someone emails the regional managers. A Slack post goes out. Meanwhile, the front-line associate is still using the version they printed last quarter.
Training content is scattered. Regulatory changes are frequent. And internal knowledge lives in pockets.
With SWIRL, trainers don’t chase updates—they connect them. SWIRL searches the LMS, the file system, the intranet, the shared folders, and the message threads. New hires can ask what are the current credit limits on secured cards? and get the right answer, with the right source, and a timestamp that proves it’s current.
One conversational interface. Role-aware. Secure. Trustworthy. No more guessing.
Conflicting systems, conflicting messages
A customer gets a text about a missed payment. Later that day, they receive a congratulatory email that their credit card application was approved. Later still, a call center rep tries to upsell them on a product they’re about to default on.
That’s what scattered data does. It breaks trust. SWIRL prevents that by stitching systems together at the search layer—without fusing them into one brittle whole. It lets agents retrieve relevant insights across systems while respecting boundaries and preserving intent.
So when an agent sees that a customer was hit by a natural disaster and marked for assistance, they don’t accidentally send a collections notice. They respond like a human would, because the AI had enough context to act like one.
Don’t gamble on a data transformation project when you just need answers
The worst part of centralization isn’t just the complexity. It’s the risk. You spend millions and change your architecture just to find out whether it might work.
SWIRL doesn’t ask for that kind of faith. You don’t need to restructure your systems. You don’t need to move your data. You don’t even need to wait.
Install it on-premises. Point it at your systems. And let your agents start working with what you already have.
You get better answers. Faster decisions. Fewer surprises. And a lot less regret.
To find out how SWIRL can help you request a customized demo today!