Conversational AI for Healthcare Providers
Front-desk teams at clinics and practices answer the same questions every day: opening hours, preparation instructions, appointment changes. A conversational AI assistant can handle these routine, non-clinical requests at any hour and pass everything else to staff.
This is an example project. It shows how we would approach this kind of work in healthcare; it does not describe a specific client. Results depend on your process and data, and we agree on how to measure them with you before starting.
Common Challenges
- Phone lines and inboxes are busy with routine, non-clinical questions.
- Patients cannot get answers or change appointments outside opening hours.
- Staff time goes to repetitive admin instead of patients in the building.
- Patient data must be handled carefully and only by the right systems.
Our Approach
We set up an Aurora conversational agent trained on your approved information (services, preparation guides, policies) and connected to your booking system. It handles administrative requests only, never gives medical advice, and hands patients to staff whenever a question is clinical or sensitive.
- Answers to common administrative questions from your approved content.
- Appointment booking, rescheduling and reminders through your scheduling system.
- Clear hand-off to staff for clinical, urgent or sensitive conversations.
- Multilingual replies with a consistent, friendly tone.
Agents used: Aurora AI customer support agent
Typical Rollout
Discovery
Map the current process, systems and data, agree on the baseline numbers and how success will be measured.
Pilot build
Build and connect the agent for one scope: the ten most common administrative questions on one channel. Set permissions, guardrails and hand-off rules.
Supervised pilot
Run on real cases with a person reviewing the agent's work, tuning it until results are reliable.
Review and scale
Compare results with the baseline and extend to more teams, sites or tasks only if the pilot clearly pays off.
Timings are indicative and depend on your systems and scope.
What We Measure
We record these before the pilot starts and compare them afterwards, so you can see whether it worked.
- Share of routine requests resolved without staff
- Response time outside opening hours
- Missed-appointment rate
- Staff hours spent on routine calls
Explore This for Your Business
Tell us about one process that takes too much of your team's time. We'll tell you honestly whether AI can help and what a pilot would look like.