AWS Healthcare United States

Availity

IT Operations Automation

In spring 2023, Michael Privat, chief architect and chief data officer at healthcare technology company Availity , started exploring how artificial intelligence (AI) could transform software development.

20 years
31 percent
33 percent
4 days

Reported impact

Business outcome

Availity’s approach to AI incorporation has changed how its engineers work. Rather than simply using AI for code completion, the company has created an environment where AI acts as an intelligent programming partner, handling routine knowledge work so that engineers can focus on innovation.

Solution

In spring 2023, Michael Privat, chief architect and chief data officer at healthcare technology company Availity , started exploring how artificial intelligence (AI) could transform software development. After deploying Amazon Q Developer to a few engineers, Availity saw that there were also use cases beyond code completion. Availity’s developers use the embedded chat to pair programs through complex solutions; typically, a developer suggests a few options, and then Amazon Q Developer provides the implementation details. In one example, an engineer resolved an issue in one 30-minute interaction with Amazon Q Developer rather than the week it would have taken previously. Because all Availity’s data was stored on AWS, the company quickly realized that it could use Amazon Q Developer to streamline many other development tasks, such as writing documentation and conducting security assessments.

Data flow

Application logic runs on Amazon Bedrock and is surfaced through Amazon Q Developer, Amazon Q Business.

Solution architecture

3 components · 2 layers
  1. Compute
    • Amazon Bedrock Hosts the foundation models and generative AI application logic.
  2. Serving
    • Amazon Q Developer Assists engineers with code generation, troubleshooting, and modernization tasks.
    • Amazon Q Business Indexes enterprise content and answers employee questions across internal systems.

Architecture clues

  • Amazon Q is completely different from just having an AI chatbot or an AI assistant in your integrated development environment.
  • This makes for great results.” Amazon Q is completely different from just having an AI chatbot or an AI assistant in your integrated development environment.

Evidence from the source

After deploying Amazon Q Developer to a few engineers, Availity saw that there were also use cases beyond code completion.
Availity operates an encrypted solution that connects medical providers with health plans across the United States, serving as a critical intermediary in healthcare.
Availity’s developers use the embedded chat to pair programs through complex solutions; typically, a developer suggests a few options, and then Amazon Q Developer provides the implementation details.
In spring 2023, Michael Privat, chief architect and chief data officer at healthcare technology company Availity , started exploring how artificial intelligence (AI) could transform software development.
The healthcare industry is traditionally slow to adopt new technology, but Availity has taken a progressive approach.
Through a series of LinkedIn posts, he detailed his vision of a “Scrum Team of the Future”—one where AI bots could handle routine knowledge work, freeing engineers to focus on creative problem-solving and innovation.
Transparency Evidence & methodology 72/100 reference value · 87% confidence · 1 source

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 value72/100
  • 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 specificity12/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    6 direct source quotes retained.
  • Date provenance8/10
    The publication date comes from publisher-controlled metadata.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    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. AWS

    Availity customer story

    First-party
    https://aws.amazon.com/solutions/case-studies/availity-q-case-study/
    Source type
    Vendor-published customer story
    Published
    Feb 27, 2025
    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

Date evidence

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.