Microsoft Healthcare United States

Veradigm

Customer Service Automation

Veradigm is a top provider of healthcare data and tech solutions for payers, providers, and life sciences—including billing services via its Practice Fusion EHR platform. It was fielding high volumes of basic medical billing questions. To help customers get faster answers, Veradigm used Azure AI Search, Azure OpenAI Service, and more in a Zammo.ai software solution to develop Billerbot. The generative AI–powered self-help chatbot is programmed to field basic queries about medical terms, processes, and billing.

As of February 2024, Billerbot appeared to be deflecting 5 percent of billing queries.
I thought, maybe if we insert conversational AI into the Practice Fusion product, we could deflect a portion of these questions ....” Ian Maurer, Vice President of Development, Veradigm Discover more details CUSTOMER PARTNER Zammo.ai PRODUCTS Azure AI Search Azure Operator Call Protection ORGANIZATION SIZE 1,000-9,999 employees COUNTRY United States BUSINESS NEED Artificial Intelligence INDUSTRY Health Provider Explore related stories Stories in this industry Stories about this customer Showing 32 of 98 categories Showing 1-2 of 2 slides Previous slide Next slide We are Microsoft Empowering others Our mission is to empower every person and every organization on the planet to achieve more.
Veradigm has a long-term goal of deflecting 10–15 percent of support requests.

Reported impact

Business outcome

To help customers get faster answers, Veradigm used Azure AI Search, Azure OpenAI Service, and more in a Zammo.ai software solution to develop Billerbot. Reducing support calls with Billerbot Billerbot made its debut in 2023, less than a year after the idea was pitched.

  • Customer Experience
  • Speed to Market

Solution

Veradigm used Azure OpenAI Service, Azure AI Search, Microsoft Dynamics 365 to support customer and agent interactions with AI-assisted automation. Veradigm is a top provider of healthcare data and tech solutions for payers, providers, and life sciences—including billing services via its Practice Fusion EHR platform. It was fielding high volumes of basic medical billing questions. To help customers get faster answers, Veradigm used Azure AI Search, Azure OpenAI Service, and more in a Zammo.ai software solution to develop Billerbot. The generative AI–powered self-help chatbot is programmed to field basic queries about medical terms, processes, and billing. Key implementation elements included Azure OpenAI Service generates natural-language responses and task automation for the solution; Azure AI Search retrieves enterprise content so answers stay grounded in customer data; Microsoft Dynamics 365 provides the common business process layer that standardizes operations; Microsoft Azure...

Data flow

Customer questions enter the assistant from web, voice, or messaging channels; the ai layer interprets intent and generates responses or actions; answers or next steps are returned to customers, agents, or clinicians through the front-end experience.

Solution architecture

4 components · 2 layers
  1. Compute
    • Azure OpenAI Service Generates natural-language responses and task automation for the solution.
    • Azure AI Search Retrieves enterprise content so answers stay grounded in customer data.
    • Microsoft Azure Hosts the application, data, and integrations on scalable cloud infrastructure.
  2. Orchestration
    • Microsoft Dynamics 365 Provides the common business process layer that standardizes operations.

Architecture clues

  • Emphasizes secure enterprise access to data and AI capabilities.
  • Operates with real-time or near-real-time telemetry and analytics.

Evidence from the source

As of February 2024, Billerbot appeared to be deflecting 5 percent of billing queries.
To help customers get faster answers, Veradigm used Azure AI Search, Azure OpenAI Service, and more in a Zammo.ai software solution to develop Billerbot.
To help customers get faster answers, Veradigm used Azure AI Search, Azure OpenAI Service, and more in a Zammo.ai software solution to develop Billerbot. Reducing support calls with Billerbot Billerbot made its debut in 2023, less than a year after the idea was pitched.
Veradigm has a long-term goal of deflecting 10–15 percent of support requests.
Veradigm is a top provider of healthcare data and tech solutions for payers, providers, and life sciences—including billing services via its Practice Fusion EHR platform. It was fielding high volumes of basic medical billing questions. To help customers get faster answers, Veradigm used Azure AI Search, Azure OpenAI Service, and more in a Zammo.ai software solution to develop Billerbot. The generative AI–powered self-help chatbot is programmed to field basic queries about medical terms, processes, and billing.
Transparency Evidence & methodology 70/100 reference value · 95% confidence · 2 sources

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value70/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence95%
  • Source authority25/25
    The deployment is described by the adopting organization or a government source.
  • Claim traceability23/25
    11 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency9/10
    2 source references document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Microsoft

    Veradigm customer story

    First-party
    https://www.microsoft.com/en/customers/story/1752451948864129472-veradigm-azure-openai-service-health-provider-en-united-states
    Source type
    Vendor-published customer story
    Published
    Apr 3, 2024
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date
  2. U.S. Securities and Exchange Commission

    Veradigm Inc. Form 10-K for the fiscal year ended December 31, 2024

    Government
    https://www.sec.gov/Archives/edgar/data/1124804/000119312526239413/mdrx-20241231.htm

    As of December 31, 2024, we had approximately 2,598 employees, with approximately 1,774 employees in the United States and 824 employees located outside of the United States.

    Source type
    Government or regulatory registry
    Supports
    • Company size

Date evidence

  • Published on source page Apr 3, 2024 · Microsoft · First-party
    Open date source
Not separately sourced Industry, Region. Treat these normalized attributes as lower-confidence until a dedicated source is added.