Customer support · Production

The Flossery replaces a human answering service with Upfirst AI to document every patient call

The problem

As The Flossery grew, the front desk could not keep up with high call volume, and a human answering service brought in to help was expensive, produced garbled messages with wrong phone numbers, and still failed to deliver accurate patient information to the team.

First attempt

A human answering service proved costly and unreliable — it produced garbled messages and wrong phone numbers and was too expensive to justify.

Workflow diagram · grounded in source
1
Incoming patient call
trigger
“Upfirst started handling incoming calls”
2
AI answers and collects info
ai_action
“The AI answers patient questions, collects information”
3
Text caller details
output
“can even text callers details like new patient policies before the team calls back”
4
Tag call by type
routing
“The system tags each call by type, so the front desk can quickly see which calls are scheduling requests versus general inquiries”
5
Notify team with summaries
output
“Yasmin and her team get notifications through email and text with full summaries of each interaction”
6
Team reviews and calls back
human_review
“It's all in written evidence of who we need to call back”
Reported outcome

Every patient call is now documented with full summaries sent via email and text, no missed calls are lost, and the owner can hold the team accountable for follow-up.

Reported metrics
Missed call capturenot lose any missed calls
Call documentationevery call is now documented
Team accountabilityhelps me keep the team accountable
Reported stack
Upfirst
Source
https://upfirst.ai/customers/the-flossery
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Every patient call is now documented with full summaries sent via email and text, no missed calls are lost, and the owner can hold the team accountable for follow-up.

What tools did this team use?

Upfirst.

What results were reported?

Missed call capture: not lose any missed calls; Call documentation: every call is now documented; Team accountability: helps me keep the team accountable (source-reported, not independently verified).

What failed first in this deployment?

A human answering service proved costly and unreliable — it produced garbled messages and wrong phone numbers and was too expensive to justify.

How is this customer support AI workflow structured?

Incoming patient call → AI answers and collects info → Text caller details → Tag call by type → Notify team with summaries → Team reviews and calls back.

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