Easy to use
The bot guides the user through a simple set of questions, helping wherever possible with contextual options right through to completion.
Case Study · Logistics
Vehicle Damage Bot
Gathering information about a vehicle's condition was previously a slow, manual, paper-heavy process. Information would be captured on a form using a “splat”, with images taken and merged manually later in the process.
This often led to inconsistent language (and potentially ambiguous data), slow update times and the manual synchronisation of information between photos and written notes.
Using a combination of Google Speech Recognition and a Conversational AI bot from pomegranates.ai, this essential data-capture process was transformed - with many additional benefits for our customer.
The impact
40 min
Time to capture damage per vehicle, before
< 1 min
Time to capture damage per vehicle, after
Paperless
Real-time updates straight into backend systems
Key features
Multi-modal
Free-form text, speech and touch interfaces let users enter information even in noisy environments.
Disambiguation & domain language
Not specific enough? The bot's AI suggests answers based on previous inputs.
It also handles domain-specific terminology - e.g. “passenger door” becomes “Did you mean nearside front door or nearside rear door?”
Real-time backend updates
Once captured, backend systems were updated immediately. Slow, cumbersome, paper-heavy processes became paperless overnight.
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