AI is Making Enterprise Search Relevant Again
For years, enterprise search was a punchline. Search inside companies rarely worked well. Employees duplicated work because they couldn't find what同事 already built.
Large language models changed the equation fundamentally.
The Old Problem
Traditional enterprise search relied on keywords. You typed words, got pages containing those words.
This failed for obvious reasons:
- Synonyms mattered: "HR" and "human resources" are the same
- Context mattered: "budget" means different things in different departments
- Structure mattered: information in PDFs, wikis, and messages needed different handling
Companies invested millions in search that still didn't work.
The LLM Transformation
LLMs enable semantic search—understanding meaning, not just matching text.
Now employees can search conversationally:
- "How do I set up benefits?"
- "What's the process for approving expenses?"
- "Who worked on the Q3 marketing campaign?"
The system understands intent and finds relevant results across all company knowledge.
Beyond Basic Search
The real opportunity isn't just finding documents—it's creating knowledge assistants.
Glean and similar tools combine search with:
- Conversational interfaces
- Personalized results based on role and permissions
- Direct answers to questions, not just links to documents
- Integration with company workflows
The Customization Requirement
Foundation models like GPT-4 provide strong starting points. But enterprise search requires more.
Instruction tuning shapes models for company-specific terminology and needs.
Enterprise integration connects to internal systems, wikis, and databases.
Security and permissions ensure employees only see what they're allowed to access.
This customization is where competitive advantage forms.
Why It Matters Now
Several factors converged:
- LLMs became capable enough to understand complex queries
- Companies accumulated enough digital knowledge to make search valuable
- Remote work made finding institutional knowledge harder
- Competition for efficiency demanded better knowledge access
The Takeaway
Enterprise search represents AI's practical impact on daily work. When employees find information faster, they work more efficiently.
The category went dormant because the technology couldn't deliver. LLMs changed that. Now the question is which company captures the opportunity—and whether legacy players can adapt.
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