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Find What Matters—Instantly, Securely, and Without Moving Data The modern enterprise is drowning in data. But finding the right insight at the right time? That's still a massive challenge.

AI-driven enterprise search is rapidly evolving, reshaping how businesses access and leverage knowledge. As organizations deal with fragmented data, operational inefficiencies, and increasing AI adoption, the need for smarter search capabilities has never been greater.

Imagine having the power of ChatGPT, but completely under your company's control — working securely within your own systems, accessing your data, and tailored to your specific needs. That's the promise of on-premises AI.

The modern enterprise is drowning in data. Every email, document, Slack message, database entry, and meeting transcript adds to the flood of new information. Yet, when it comes time to retrieve that information, we struggle to find what we're looking for.

SQL has been the language of database access since the 1970s. Like the story of Babel, it has divided into numerous dialects — PostgreSQL, MySQL, SQL Server, Oracle — each one subtly different from the others.

What if AI could search data where it already resides? From AI to AI Search is a small jump in concept, a giant leap in reality. Organizations have struggled to implement effective internal AI search because of one major obstacle: ETL.

The goal of enterprise AI Search is to make it easier for us to find important information—while not making it easier for unauthorized people to find it. AI search is transforming how enterprises access and leverage information.

Google does it, Apple is doing it, and so are OpenAI and Perplexity. They're all leveraging AI summaries—bringing together the most relevant search results and using AI to deliver concise answers. Your employees are already using these tools, both at home and in the workplace.