Voice intake audit and pivot to ambient capture

Pilot tested, evaluated, and a clear architectural recommendation delivered honestly.

Same network as the CV parser engagement above. Roughly 60% of qualified leads come through phone calls, 30% in person, 10% across Teams and Google Meet.

Problem

The richest lead information was locked inside conversations nobody wrote down. A good voice conversation would happen, the lead would be qualified, and the next day someone would try to reconstruct the call from memory to update the CRM. Budget signals, timeline, role specifics, cultural fit: captured if the team member was disciplined, missed if they were not. Variability across the team was large. Inconsistent discipline cost real deals. The ask: an automated path from voice to CRM summary, without asking the people in the conversation to do extra work.

How the industry typically approaches this

Voice-to-CRM workflows have two layers. Capture (where audio gets recorded or streamed) and processing (transcription → structured data → CRM write). Processing is solved at industry scale. Capture is the hard part. A conversation might happen on a landline, on WhatsApp, face-to-face, or on a video call. Each channel has its own recording quirks, compliance rules, and UX friction.

Our approach

Designed, built, and piloted a software-first solution. Voice message created, automatically uploaded to a shared drive, transcribed, summarised, and an email with the structured intake sent back to the team member. Intake summary included action items and could drop directly into CRM. Technically the pipeline worked. The pilot revealed software-only could not reliably capture conversations across the full channel mix in use. We delivered the recommendation that came out of the pilot honestly: software is not the right centre of gravity. The right solution is a small, dedicated, always-available AI device per team member, paired with the same transcription and summarisation pipeline already built.

• •Pilot built, tested, evaluated
• •Architectural recommendation delivered honestly: ambient capture hardware
• •Transcription and summarisation pipeline reusable for the next phase

What the industry has achieved with similar solutions

External benchmarks from comparable deployments. Sourced and labelled as third-party evidence, not our own results.

• Academic medical centre, 8 hospitals and 60+ practices

  ActiumHealth outbound voice agents. $39M incremental annual revenue. 12x lower cost per interested patient. ActiumHealth

• Baptist Health, US health system

  Hyro AI agents. ~$1M savings in 3 months. 64% appointment-management automation. 70.5% patient identification. Hyro