Healthcare Voice AI Is Here. Is Your Agent Ready?
Welcome back to The Bluejay Times !
Let me ask you something:
When was the last time you called a doctor's office and actually got through on the first try?
Most people know this feeling. You call, you navigate the phone tree, you wait on hold, and by the time someone picks up you have already rehearsed exactly what you need to say. Now imagine the person on the other end is a voice agent, and imagine that voice agent gets something wrong.
A missed appointment is an inconvenience. A missed urgent symptom is a patient safety issue. A prompt regression that quietly breaks after a model update could mean a patient who needed to be seen urgently gets booked three weeks out instead. Nobody catches it until someone calls to complain or worse, does not call at all.
Healthcare is the one industry where the margin for error in voice AI is essentially zero, and yet voice agents are being deployed across healthcare faster than most teams are testing them.
This is the problem that keeps coming up in every conversation we have with teams building in this space. What they do not know is whether it still works after the last model update, whether it handles the edge cases that never showed up in testing, whether the patient who calls from a noisy waiting room gets the same experience as the one who calls from a quiet office.
Manually calling your agent a few times catches obvious bugs. It will not catch the patient who changes their mind mid-call, the mis-transcription that books the wrong provider, or the prompt regression that silently breaks urgent call handling after a model update.
That is exactly what Bluejay is built for, and this week we built something with Twilio to show exactly what rigorous voice AI testing looks like in a healthcare context.
Together we put together a full guide on building and testing a patient appointment scheduling agent, one that handles bookings, reschedules, cancellations, and urgent slot requests.
Bluejay runs simulations before launch, replicating the messy real world scenarios that break agents in production. The patient who changes their mind mid-call. The mis-transcription that books the wrong provider. The prompt that quietly stops working after an update.
You catch the failures before your patients do.
Read more about it below in Build and Test a Patient Appointment Scheduling Agent with Twilio and Bluejay!
As a recap:
- Bluejay is a testing and monitoring platform for Conversational AI agents. Companies ranging from Fortune 10 enterprises to fast-growth startups in the Silicon Valley use Bluejay to make sure their voice and text agents work in production (monitoring) and development (testing) environments.
- Our team, now ten strong, works around the clock to make sure your agent behaves when talking to customers.
- This newsletter is 100% human written. It always has been, and it always will be. Ask yourself about what you are consuming. If the writer hasn't read it, why should you?
Give Humanity the tools to trust Artificial Intelligence.
Announcements
Heres what happened at Bluejay last week:
- Rohan, Faraz, and Ryan headed to CCW in Las Vegas this week to connect with the people building the future of customer communications!
- Bluejay partnered with Twilio to release a joint guide on building and testing a patient appointment scheduling agent!
- The team pushed 54,794 lines of code this week to make Conversational AI more reliable!
Build and Test a Patient Appointment Scheduling Agent with Twilio and Bluejay
Bluejay teamed up with Twilio to release a joint guide on building and testing a patient appointment scheduling agent using Twilio Programmable Voice, Conversation Relay, and Bluejay.
Voice AI in healthcare has no margin for error. A missed appointment is an inconvenience. A missed urgent symptom is a patient safety issue.
The agent handles bookings, reschedules, cancellations, and urgent slot requests. Bluejay plugs in at both ends. Simulations run hundreds of patient calls before launch, then every real call gets monitored in production.
The simulations replicate the messy stuff. The patient who changes their mind mid-call. The mis-transcription that books the wrong provider. The prompt regression that quietly breaks urgent call handling after a model update.
You catch the failures before your patients do.
The full walkthrough is live on the Twilio blog. Check it out below!
Deepti Naidu and Rohan Vasishth
Behind the Build
What is new this week at Bluejay ?
- We shipped a full Audio Quality suite. You can now see a six axis quality radar per conversation covering loudness, fidelity and more, plus a Tyto risk score so you can spot bad sounding calls at a glance.
- You can now compare two agents side by side to see which one actually performs better across runs.
- Retell, Vapi and ElevenLabs now auto-sync with Bluejay. Your agents stay up to date without manual exports. One click and you are good.
- Bulk actions are here. Select, delete, activate alerts, update and duplicate digital humans, add teammates, and upload digital humans via CSV all at once.
Feature Spotlight:
This week Bluejay AI got a significant upgrade.
It can now run real executable skills directly inside the platform. That means when you ask it to do something, it does not just tell you how. It actually does it.
Ask it to run a simulation and it kicks one off. Ask it to analyze your failures and it pulls the results, finds the patterns, and surfaces what broke. Ask it to apply a prompt fix and it makes the change directly without you having to copy anything across.
The in-app assistant went from a question answering tool to an action taking one. If you have been using Bluejay AI to ask questions, go back in and try asking it to do something instead. The difference is worth experiencing firsthand.
Give it a try and let us know what you think!
That's all for now. I'll see you next time!
Azfar Khan
Storyteller @ Bluejay
