The use case: how Signify Health deploys Observe.AI
Signify Health's contact center uses Observe.AI's Real-time Agent Assist to give agents live prompts, smart scripts and alerts during member calls, which supports onboarding, coaching and objection handling. It also uses Auto QA to analyze far more calls for quality trends than manual review allowed.
More reported results
Figures published in Observe.AI’s case study. They are not independently measured by usedby.
We’ve seen that upwards of 34% just in the short time that we’ve been using Agent Assist.
Likewise, by adopting Observe.AI’s Auto QA, the quality team has gone from manually reviewing around 70,000 calls a year to analyzing about 65 million.
In the customer’s words
Now we can guide and prompt them through tough calls. You can hear it in their voices that they feel more at ease.Observe.AI users in HealthTech & Digital Health
Companies in the same sector, with public evidence.
MaxorPlusConfirmed
Personify HealthConfirmed
Simple Online HealthcareConfirmed
TranscarentObservedGo straight to the source
Based on Observe.AI’s published case study. We check the public evidence; the results are reported by the vendor.
observe.ai- Last checked
- Oct 10, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 70% to 82%Checked
The figure is on the page; its label is our wording.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Signify Health.
- Signify Health uses Observe.AIChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
By using Observe.AI to correlate prompt usage to business outcomes, Signify Health increased its speed to proficiency—the percentage of new hires reaching an acceptable level of performance—from 70% to 82% in one year.