Turning patient voice feedback into AI-processed insight
FeedbackCompanion turns scanned voice feedback into AI transcriptions, summaries, and sentiment in three steps — giving healthcare teams a real-time view of themes by department and employee so urgent concerns get addressed before they escalate.
The challenge
- Hospitals and healthcare organisations struggled to address immediate concerns and negative feedback quickly enough.
- There was no systematic way to monitor feedback, making it hard to assess whether changes were working.
- Long-term feedback trends went untracked, weakening strategic decisions and any real understanding of patient satisfaction.
What we did
- FeedbackCompanion opens with a QR scan on any device — the whole flow is three steps: scan, record feedback, send.
- AI algorithms transcribe each voice message, summarise the full content, and extract key topics and sentiment.
- A dashboard turns AI-processed audio into statistics categorised by department and employee, with real-time trend tracking.
- Deployment is fast and the tool needs almost no log-ins, so it drops into a busy clinical setting with minimal friction.
Results
- 3steps from scan to submitted feedback
- 100%of voice messages transcribed and summarised by AI
The context
Hospitals and similar organisations struggle to act on patient feedback fast enough. Urgent concerns and negative comments arrive with no systematic way to capture them, so responses lag and reputational risk builds.
The deeper gap is monitoring. Without a structured record, it is hard to tell whether a change actually improved anything, and long-term trends in satisfaction stay invisible, which weakens every strategic decision that depends on them.
What we built
FeedbackCompanion turns spoken feedback into structured insight. A patient scans a QR code on any device and the whole flow is three steps: scan, record, send. No app to install, almost no log-ins.
- AI transcription of every voice message, with a full-content summary.
- Automatic extraction of key topics and sentiment from each piece of feedback.
- A dashboard of statistics from AI-processed audio, categorised by department and employee.
- Real-time trend tracking so emerging issues surface quickly.
How it works in production
The recording is transcribed, summarised, and scored for sentiment, then rolled up by department and employee. A manager opens the dashboard and sees not a pile of raw comments but the themes that matter and where they are coming from, updating as new feedback lands.
The outcome
Urgent concerns can be addressed before they escalate, and quality can be tracked department by department as changes are made. Teams can recognise staff who consistently receive positive feedback, spot long-term trends for planning, and pinpoint process inefficiencies worth fixing.
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