AI Products

AI Clinician Assistant

AI Contact Center

AI Contact Center Analytics and Intelligence solutions use AI to evaluate contact center performance and to provide solutions to improve contact center performance or efficiency. These vendors typically emphasize strong capabilities in analyzing large volumes of voice and text contact center data. Use cases include:
- Agent performance evaluation and measurement, and generation of feedback
- Analysis of encounter content and generation of solutions to address customer needs
- Customer sentiment analysis

AI Contact Center Intelligence

AI Conversational Chat encompasses the next generation of chatbots. These companies are using more advanced NLP, machine learning and gen AI to tackle full “front desk” functionality and create a personalized experiences in functions including:
- Scheduling and appointment management
- Prescription refills
- Triage and call routing
- Intake
- Billing

Further, some conversational chat solutions are increasingly focused on clinical capabilities to better engage patients and extend the reach of care teams:
- Patient engagement and education
- Care navigation and care management
- Medical interviewing and risk analytics

AI Conversational Chat

Patient-Facing AI Phone Calls includes products that enable AI-based interactions with patients over the phone. Most products in this space are focused on inbound calls, but there are some outbound call capabilities for appointment reminders and other administrative tasks. Some products will also have web- and chat-based capabilities as well. Companies in this category are differentiated by conversational capabilities powered by advanced AI included NLP, generative AI and machine learning. 

Vendors in this category have varying coverage of use cases, including:
- Appointment scheduling
- FAQ for hours, location, parking, etc.
- Prescription Refill requests
- IT Helpdesk for patient-facing IT
- Department and Provider Search
- Patient billing

Differentiation in this space tends to come from factors including: 
- Ability to manage complicating factors like background noise, varied accents, and off-track conversations 
- Fluid conversational ability with a human-sounding AI, unlike traditional IVR call trees
- Support for multiple languages, especially for a wider set of patient demographics
- Fallback support with human agents when the AI isn’t getting the job done
- Technical considerations including data privacy, security, and EHR integration quality
- Analytics capabilities to help track success rates, errors, and unknown FAQs.

Patient-Facing AI Phone Calls

Payer-Facing AI Phone Calls includes products that enable AI-based interactions with payers over the phone. Generally, payer-facing companies will tend to be making outbound phone calls, but there may be some inbound-calling capabilities as well. Some of the common use cases for products in this category include: 

- Eligibility and verification of benefits
- Prior authorization
- Claims status checks
- Denied claims appeals
- Credentialing and provider management

Because the payer environment is generally much more controlled than a patient-facing environment, some of the differentiating factors in this space include:

- Fallback support with human agents when the AI isn’t getting the job done
- Technical considerations including data privacy, security, and EHR integration quality
- Caller dashboard to enable requesting outbound calls and viewing call results.
- Analytics capabilities to help track success rates and potential errors across calls.
- Payer-specific modules to handle the IVR tree and agent script, or
- Low-code script builder to enable customized calling procedures

AI Contact Center Agent Assistants