Can you explain the difference between semantic search and keyword search for internal company knowledge, and when each one makes sense?

Yes — here’s the practical difference:

Keyword search

Keyword search looks for the exact words you type, or close variants. It works well when you know the specific term used in the document.

Example:
Searching for “Q3 headcount plan” returns documents containing those words.

Good for:

• Exact names, IDs, error codes, product names
• Policies or docs where terminology is consistent
• Fast, transparent, predictable retrieval
• Cases where users know the right phrase

Limitations:

• Misses results when the document uses different wording
• Struggles with synonyms and paraphrases
• Can fail when users ask in natural language instead of using internal jargon

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Semantic search

Semantic search looks for the meaning behind the query, not just the literal words. It uses embeddings / vector similarity to find documents that are conceptually related.

Example:
Searching for “how do we handle employee offboarding?” might return docs titled:

• “Termination checklist”
• “Access removal procedure”
• “Exit process for contractors”

even if those words don’t match directly.

Good for:

• Natural-language questions
• Finding docs when users don’t know the exact wording
• Surfacing related concepts and paraphrases
• Broad internal knowledge bases with inconsistent terminology

Limitations:

• Less precise for exact terms
• Can return “close enough” results that aren’t actually the right answer
• Harder to explain why a result was returned
• Often benefits from combining with other filters or keyword matching

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When each makes sense

Use keyword search when:

• Users know the exact term
• Precision matters more than conceptual matching
• You need simple, explainable results
• Your corpus is structured or standardized

Examples:

• HR policy lookup by policy name
• Searching for an incident ticket number
• Finding a specific product feature or code module

Use semantic search when:

• Users ask questions in plain English
• The same concept is described in many different ways
• The knowledge base is large and unstructured
• You want a more “ask a question” experience

Examples:

• “How do I request equipment for a new hire?”
• “What’s the process for changing vendors?”
• “Where do I find the latest onboarding steps?”

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Best practice: combine them

For internal company knowledge, the best system is often hybrid search:

• Keyword search for exact matches and filters
• Semantic search for meaning and recall
• Optionally rerank results using both signals

This gives you:

• Better coverage
• Better precision
• Better user experience

If you want, I can also give you:

1. a simple architecture for hybrid enterprise search, or
2. a decision matrix for choosing between keyword, semantic, and hybrid search.