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Use Case
We build AI call summary systems that transcribe every sales call, extract the structured data your CRM needs, update the deal record automatically, and send a summary to the rep and their manager, all within minutes of the call ending.
The rep finishes a call and moves to the next one. The notes are already written, the CRM is already updated, and the manager already knows what happened. No post-call admin required.
Tell us about your call note problem.
Six components that handle the full post-call workflow, from recording to CRM update to manager summary.
Connects to Zoom, Microsoft Teams, or Google Meet via Recall.ai or Rev to capture the audio. No manual recording setup required, every call is captured automatically.
High-accuracy transcription with speaker diarisation, the system knows who said what. Filler words are cleaned; the transcript is readable and searchable.
Buyer name, company, stated pain points, budget discussed, next steps agreed, objections raised, and methodology fields (MEDDIC, BANT, SPICED) are extracted into typed structured data.
Extracted fields update your Salesforce or HubSpot deal record automatically. Deal stage, next steps, and notes fields are populated without the rep opening the CRM.
A concise call summary lands in Slack or email within minutes of the call ending, for the rep as a reference and for the manager as a pipeline review aid.
Optional: each call is scored against your sales methodology (e.g., were all MEDDIC fields identified? Was a next step agreed?). Gaps surface immediately rather than at deal review.
From call end to CRM update and Slack summary, the full sequence.
Call ends
The recording is captured via your existing video conferencing platform. The system detects the call end and begins processing without any manual trigger from the rep.
Transcription
The audio is transcribed with speaker labels. The process takes two to five minutes for a 45-minute call. The transcript is stored and searchable.
LLM extraction
The transcript is processed by a structured extraction prompt that pulls the specific fields your CRM needs: deal stage, budget range, pain points, objections, agreed next steps, and any methodology-specific fields.
CRM fields updated
Extracted fields are written to the corresponding deal record in Salesforce or HubSpot. The rep can review the update in their CRM, no copy-paste required.
Summary sent to rep and manager
A Slack message or email arrives within minutes with the call summary, key takeaways, agreed next steps, and any methodology gaps flagged. The manager sees every deal update without waiting for rep notes.
The right fit is a sales team with consistent call volume and a CRM they want to keep current.
Reps spending 20% of their time on post-call admin is time not spent selling. This moves note-taking and CRM updates out of the rep's workflow entirely.
CRM data is only as good as what reps enter. When the AI fills the fields automatically, data quality doesn't depend on rep discipline. It just happens.
Forecasting and pipeline reviews require consistent data across deals. When every call produces the same structured output, reporting becomes reliable rather than dependent on each rep's note-taking style.
We’d rather say this now than after discovery.
Sales teams without a CRM or using spreadsheets
The primary value of this system is automatic CRM population. If your sales process isn't in a CRM yet, the better first investment is getting the CRM set up and your team using it before adding AI on top.
Teams with fewer than 5 calls per week
At very low call volume the time saved on notes doesn't offset the build cost and ongoing maintenance. Manual note-taking remains the practical choice.
Tell us how many calls your team has per week, which recording platform and CRM you use, and which CRM fields matter most for forecasting. We’ll reply within one business day.