SWIRL Blog

September 11, 2025

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

If your processes still run on spreadsheets and email, you’re not digital. You’re pretending. Digital transformation isn’t measured by how many SaaS apps you’ve bought. It’s measured by how seamlessly your people, processes, and data can adapt to change. Most enterprises fail that test.

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).

August 21, 2025

Teams Not Communicating? Time to Open the Data Silos!

Sharepoint. Tableau. Snowflake. MongoDB. Salesforce. The list goes on and on. Maybe your business uses only some of them, maybe it uses all of them, or maybe it uses a completely different set of applications. It doesn’t really matter.

August 19, 2025

Acting in Real-Time—Instant Insights Without the Wait

You’re driving down the highway at high speed. Suddenly, everything you see is delayed by 2 seconds. What happens? If you’re lucky, you just miss your exit. If you’re unlucky, you make the nightly news, although you may not be in a position to enjoy the publicity.

August 12, 2025

Lost in the Centralization Fog? Why A Zero ETL Model Outperforms Data Centralization for AI

Data centralization promises simplicity. In theory, you put all your data into one vector database, a lakehouse, or an advanced data fabric—and the AI just works. But in practice, it’s an illusion.