Perry Ellis · Yotpo
1.4% — conversion rate
Independently reportedRetail & e-commerce · Customer support · NLP · Scaled
Customer support
IBM · Condado
Vendor-reportedTechnology & softwareUnited StatesScaledEnterpriseNLPLive 2019
Vendor-reported. The customer is named and the numbers are quoted from the source page, but the account comes from the vendor. No independent confirmation.
Reported by condado.com (vendor self-report). Checked against the source page on 2026-09-06. 1 of 2 figures below appear on that page word for word; the rest are marked.
The problem
IBM needed to scale its healthcare call center operations to handle 75,000+ conversations per month without significantly increasing headcount, while maintaining high service quality and compliance. A key challenge was integrating IBM's Watson AI with NICE's CCaaS platform, which lacked native AI capabilities in 2019.
What was deployed
- Vendor
- Condado
- Products
- NICE CX, Watson AI
- Models
- Watson
- Technique
- NLP
- Build or buy
- Bought and customised
- Deployment
- Custom build
- Data used
- protected patient health information (PHI), medical history, prior interactions, healthcare-specific organizational intelligence, patient-provider communications
- Scale
- handled 125,000+ voice calls per hour at peak capacity
What changed
Each row is quoted from the source. Figures we could not find on the page in those words are marked — they are kept, not deleted, so you can judge them.
90%AI deflection rate
“90% AI deflection rate. Watson handled most inquiries without human intervention.”
Not found on the source page in these words · round percentage, no baseline given
125,000+voice calls handled at peak capacityat peak capacity in 2020
“Handled 125,000+ voice calls per hour at peak capacity in 2020.”
Quoted word for word from the source
significantcost savings
“Significant cost savings”
Quoted word for word from the source
would have needed to double their workforceavoided workforce increase
“IBM estimated that they would have needed to double their workforce without this AI-driven solution.”
Quoted word for word from the source
achievedregulatory compliance
“Regulatory compliance achieved”
Quoted word for word from the source
protectedpatient data protection
“Protected patient data while maintaining service quality.”
Quoted word for word from the source
ROI as stated: Significant cost savings
Difficulties and limits
- No pre-existing AI integration in NICE (in 2019), requiring custom build without pre-built APIs or AI orchestration frameworks.
- Compliance and data security for Protected Health Information (PHI) not natively supported by NICE, requiring custom encryption and authentication protocols.
- Ensuring a seamless AI-human experience, as callers had a 60% chance of hanging up if they perceived a system transfer.
- Watson's instant response times felt unnatural to human agents, requiring randomized response timers.
- Seamless call transfers without SIP Refer support, requiring manual design of silent connection transitions.
Sources
- condado.com — vendor self-report
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