The myth is persistent: before you can build AI, you have to centralize your data. Clean it. Transform it. Move it into some gleaming new architecture where everything is finally, blissfully unified. Then—and only then—can you start building something intelligent.
Here’s what actually happens: you spin up a centralization project. You model your data. You write transformation logic. You patch over differences between formats and schemas that never align. Meanwhile, systems depending on those schemas break. Reporting dashboards go dark. APIs start throwing errors. And the engineers you need to build AI agents? They’re babysitting ETL jobs.
Six months pass. You’re still modeling. The AI roadmap hasn’t moved. And the business still can’t answer basic questions without five tabs open and a manual export from Salesforce.
That’s a lot of software development work for an insurance company seeking to harness AI.
SWIRL makes data usable where it lives
No ETL. No copying. No migration. No cascade of breakages.
SWIRL installs fast. It connects to your existing environment. For an insurance company, that means customer policy data in your core platform. Historical email in Outlook. Procedures in Confluence. Contracts in PDFs. Structured. Unstructured. Legacy. Cloud. Doesn’t matter. SWIRL searches all of it, live, in place—while respecting security, access controls, and audit requirements.
Agents don’t need a clean warehouse to act. They need relevant, accurate, permission-aware context. SWIRL gives it to them.
It ain’t broke so stop fixing it
Remodeling a data environment is like rewiring your house during a blackout. You’re already in the dark, and now you’re pulling the walls apart. And when you finally flip the switch? Half the devices don’t turn on. Why not? Because they were hardcoded to expect a format you just retired.
Sure, you can fix that programmatically. Write new wrappers. Map new schemas. Rebuild your pipelines. But now you’ve added another layer of complexity. More glue code. More points of failure. And no one’s any closer to shipping an AI agent that actually helps your underwriters.
With SWIRL, you don’t touch your data models. You don’t change your app dependencies. You don’t even update your stack. Everything stays intact. You just point SWIRL at the systems and go.
Compliance doesn’t care that your data is fragmented
Financial services, insurance, healthcare; they all live under a compliance microscope. You can’t afford gaps. You can’t afford inconsistencies. You definitely can’t afford a breach.
But when your documentation is scattered across jurisdictions, branches, systems, and formats, consistency is almost impossible. Legal teams drown in PDFs. Audit teams play detective across legacy drives and chat logs. And nobody can find the escalation protocol for a cybersecurity incident because it’s buried in a legal archive from three CISOs ago.
SWIRL fixes that by turning chaos into searchability. Ask: what are the escalation steps for a cybersecurity incident? SWIRL pulls results from Confluence, email archives, training documents, and flagged legal memos—filtered by region, role, and relevance. The agent sees what it should. Nothing more. Nothing less.
Agents only need the right data, right now
An advisor needs to prep for a client call. The information is spread across Outlook, Salesforce, and an aging intranet. There’s no time to dig. SWIRL connects it all. The AI agent retrieves the latest notes, flagged complaints, last policy update, and anything marked urgent in the inbox.
An underwriter wants to check a file. The property address is in one system. The policy doc is in another. The appraisal is missing. SWIRL highlights the gap and pulls the relevant context to investigate.
Legal is preparing for a regulatory review. They need every instance of a policy across branches. They also need to know where those versions conflict. SWIRL doesn’t just find them—it points out where they’ve changed.
That’s not search. That’s operational intelligence.
The biggest blocker to agentic AI isn’t the model—it’s the plumbing
LLMs are everywhere. You’ve got the language part handled. But giving an agent access to the right data, in the right format, under the right permissions—that’s what turns a model into a system.
SWIRL is the connective tissue. It handles retrieval, ranking, filtering, and orchestration in real time. The agent asks. SWIRL answers. Securely. Confidently. Contextually.
You don’t need to wait for a data unification project that may never finish. You don’t need to replace your systems. You don’t need to convince security that this time, the vendor’s compliance story holds water.
You don’t need a new environment. You need the one you have—searchable.
Agents can’t act on what they can’t find. SWIRL fixes that. Download our white paper, request a demo, or contact us for more information!