Speech-to-Text for Knowledge Bases: Make Your Meetings Searchable

Every day, your team generates hours of spoken information—meetings, customer calls, training sessions, internal discussions. Most of it disappears into recording archives that nobody searches because nobody can. This is part of our guide to speech-to-text use cases, where we explore how transcription transforms business workflows.

The solution is surprisingly straightforward: transcribe your audio content and make it searchable. Companies using AI transcription tools report a 25% increase in team productivity, largely because searchable transcripts eliminate time-intensive information retrieval.

Why Audio Content Stays Hidden

Unlike text documents, audio and video recordings are essentially invisible to search. You can't skim a 60-minute meeting recording to find where someone mentioned a specific decision. You can't search your call archive for every mention of a particular client.

This creates several problems:

• Lost institutional knowledge: Important decisions, context, and reasoning live only in recordings that nobody revisits
• Onboarding friction: New team members can't learn from past discussions without someone walking them through hours of content
• Repeated discussions: Teams rehash the same topics because finding previous conclusions is harder than starting fresh
• Compliance gaps: When you need to prove what was said, scrubbing through recordings is slow and error-prone

The global speech-to-text market reached $5 billion in 2024 and is projected to grow to $21 billion by 2034. Much of this growth comes from organizations recognizing the value locked in their untranscribed audio.

How Speech-to-Text Enables Knowledge Search

Modern transcription turns audio into text that behaves like any other searchable document. The process typically works in three stages:

1. Transcription with Context

Quality transcription goes beyond converting speech to words. Useful knowledge base transcripts include:

• Speaker identification: Knowing who said what matters for accountability and context
• Timestamps: Link text back to the original recording so users can hear the actual moment
• Punctuation and formatting: Well-structured text is faster to scan than a wall of words

The best transcription models in 2026 achieve over 95% accuracy in good recording conditions, with some enterprise solutions reaching 96-99%.

2. Indexing and Organization

Once transcribed, content needs structure. This means:

• Tagging by meeting type: Customer calls vs. internal discussions vs. training sessions
• Linking to participants: Associate transcripts with relevant people, projects, or accounts
• Extracting key points: AI summaries can surface decisions, action items, and main topics

3. Search and Retrieval

The final step is making content findable. Effective knowledge base search supports:

• Full-text queries: Find any word or phrase across all transcripts
• Filtered searches: Narrow results by date, participant, meeting type, or project
• Semantic search: Find content by meaning, not just exact keyword matches

Practical Implementation Approaches

You have several options for building a searchable audio knowledge base:

Dedicated Transcription Tools

Standalone transcription services like Scriby focus on accuracy and export flexibility. You upload recordings, receive transcripts, and integrate them into your existing knowledge management system. This works well when you want control over where transcripts live and how they're organized.

Meeting-Specific Platforms

Tools like Otter.ai, Fireflies, and Tactiq specialize in live meeting capture. They automatically join video calls, transcribe in real-time, and build searchable libraries of meeting content. The tradeoff is platform lock-in—your knowledge lives in their system.

Enterprise Search Integration

Larger organizations often connect transcription to enterprise search tools. Amazon Kendra, Azure AI Search, and similar platforms can index transcripts alongside other documents, creating unified search across all company knowledge.

DIY Approaches

Technical teams sometimes build custom pipelines using open-source models like Whisper combined with search engines like Elasticsearch. This offers maximum flexibility but requires ongoing maintenance.

What to Transcribe First

Not all audio content has equal knowledge value. Start with:

• Customer calls: Sales conversations, support interactions, and account reviews contain insights that benefit multiple teams
• Decision meetings: Discussions where important choices were made and the reasoning matters
• Training sessions: Content designed to transfer knowledge is worth preserving
• Expert explanations: When someone explains a complex topic well, capture it for reuse

Skip routine status updates and meetings that could have been emails—transcribing everything creates noise that makes search less useful.

Common Pitfalls to Avoid

Transcribing Without Organizing

Thousands of untagged, unlabeled transcripts aren't much better than untranscribed recordings. Plan your tagging and metadata strategy before you start transcribing at scale.

Ignoring Audio Quality

Transcription accuracy depends heavily on recording quality. Poor audio produces poor transcripts that mislead searchers. Invest in decent microphones and encourage participants to speak clearly.

Forgetting Access Controls

Not everyone should see every transcript. Customer conversations may contain sensitive information. HR discussions are confidential. Build access controls from the start rather than retroactively restricting content.

Getting Started

Building a searchable audio knowledge base doesn't require a massive upfront investment. Start small:

1. Pick one content type: Customer calls or weekly team meetings are good starting points
2. Transcribe a month's worth: Enough to test search value without overwhelming commitment
3. See if people search: Track whether the transcripts actually get used before scaling up

Scriby's pay-as-you-go model works well for this experimental phase—transcribe what you need without subscription commitments, then scale based on results.

The Bigger Picture

Searchable transcripts turn spoken knowledge into a lasting organizational asset. Instead of information evaporating after meetings end, it becomes findable, quotable, and reusable. New team members can learn from years of accumulated discussions. Decisions come with documented reasoning. Customer insights spread beyond the people who heard them firsthand.

The technology to make this happen is mature and accessible. The main barrier is simply starting—picking content worth transcribing and building the habit of searching audio alongside text.