SWIRL Blog

October 7, 2025

Need Answers to Your Questions? Don’t Rewire the Factory

Manufacturing systems weren’t built for flexibility. They were built to last. MES, ERP, QA, maintenance logs, part libraries, inventory files, scanned PDFs from 2007—everything has a purpose, and almost none of it was designed to talk to each other. Still, that hasn’t stopped consultants from telling you to centralize. Rip it out. Rebuild it. Push everything into a shiny vector database and wrap a chatbot around it. But to get there, you’ll need months of ETL, schema unification, pipeline testing, and governance meetings. And at the end? You get to find out if it even works.

September 25, 2025

From Compliance to Contracts: How Federated AI Search Delivers Legal ROI

Legal departments rely on Westlaw and LexisNexis for regulatory intelligence and precedent, but critical internal documents, contracts, policies, compliance reports, sit in silos across SharePoint, email, ERP, and CRM. The result: fragmented workflows and slow turnaround.

September 23, 2025

SWIRL AI Warehouse: Real-Time Analytics Without the Migration Tax

For years, enterprises have been told the same story: if you want modern analytics, you need to copy, clean, and move your data into a shiny new cloud platform. The result? Expensive migrations, endless ETL pipelines, and dashboards powered by yesterday’s data.

September 11, 2025

Future-Fit or Bust: Building an Enterprise That Can Actually Keep Up

September 9, 2025

Legal Data, Legal Pressure

Few industries are as data-intensive or as high-stakes as the legal sector. Attorneys face overflowing volumes of case law, contracts, filings, emails, and regulatory updates. Yet the reality is grim: according to Thomson Reuters, 72% of legal professionals say finding the right information quickly is their biggest productivity challenge.

September 4, 2025

SWIRL Enterprise 4.3: Deep Linking, Ratings, Japanese Language Support & More

Team SWIRL is excited to announce the release of SWIRL AI Search 4.3, Enterprise Edition — delivering more transparency, feedback, and global language support to enterprise AI search.

September 4, 2025

Be Careful What You Wish For—Or You Won’t Like the SQL

How is a raven like a writing desk? Actually, I have no idea. But I do know how an LLM is like a genie. It’s all about wishes. Remember all those tales about wishes gone awry? The stories of the Fisherman and His Wife and The Monkey’s Paw are but two examples. In both stories, wishes that are not framed very carefully lead to outcomes that range from comedically awkward to horrific. Asking a genie to grant a wish is fraught with risk.

September 2, 2025

Centralizing Your Data—The Slowest Way To Make It Useful

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.

August 28, 2025

Stop Rebuilding the Stack. Start Getting Answers.

Every time a company tries to “get serious” about AI, the same pattern plays out: centralize the data, deploy a vector database, spend months re-architecting infrastructure, and then pray that something useful comes out the other side.

August 26, 2025

Another One Bites the Dust—RIP Vector Databases

It’s been a rough time for vector databases. A wonderful, hot technology that’s suddenly run into some headwinds. Or maybe a small hurricane would be more accurate. That’s never happened to a hot technology before, right? Well, other than BigQuery, Hadoop, Google Glass, Second Life, Quibi. And mainframes. And a few others, enough to Segway to my next point (yes, the Segway failed too).