AI Call Transcription

A recording is only useful if someone listens to it. Transcription turns every call a voice agent handles, and every call it transfers, into text a manager can search, a CRM can store and an analytics job can count. In a voice agent it is a by-product of the same speech recognition that drives the conversation, captured for after the call rather than during it.

How it works. The call audio is split by channel so the caller and the agent are labeled separately. A speech-to-text pass produces the transcript with timestamps; a post-call pass usually re-runs recognition on the full recording for higher accuracy than the live stream. A language model then writes a short summary and extracts fields: reason for call, outcome, follow-up owed, sentiment. The transcript, summary and fields are attached to the call record and pushed to the CRM or sent by email.

Why it matters for operations. Coaching, disputes and compliance all depend on knowing what was said. A manager can review twenty calls in the time it takes to listen to two. A disputed booking can be settled by searching for the moment the caller agreed to it. Recurring questions surface in search before they surface in complaints. And transcripts of transferred calls mean the person receiving the call reads the context instead of asking the caller to repeat it.

Example. A real-estate brokerage runs a voice agent on its listings line. Each morning the office manager searches the previous evening's transcripts: "parking" appears in eleven calls about one building, so the listing copy is updated that day. One caller mentioned a competitor's open house; that transcript goes to the listing agent with the summary field "interested, wants Saturday viewing". The CRM record for the caller already holds the transcript, so the follow-up call starts with context instead of a cold introduction.

Call transcription vs sentiment analysis. Transcription produces the words. Sentiment analysis reads those words, and sometimes tone, to score how the caller felt. One is the raw material; the other is a derived signal, and it is only as reliable as the transcript beneath it.

What to measure.

• Word error rate on a monthly sample of calls, checked against the recording.
• Speaker attribution errors, where the caller's words are credited to the agent or the reverse.
• Summary accuracy, spot-checked by a person against the full transcript.
• Time from call end to transcript availability in the CRM.
• Retention period and who can open transcripts.

Recording and transcribing calls is regulated. Several US states require consent from every party on the call, and health information in a transcript falls under HIPAA for covered entities and their business associates. Put the disclosure in the greeting and set a retention period that matches your obligations.

On Botcadence, the transcript travels with the handoff when a call is passed to a person, and data is encrypted with AES-256 at rest and TLS 1.2+ in transit. See voice agents and conversation analytics.