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Microsoft Automotive United Kingdom

JATO Dynamics

Data Lake / Data Warehouse Modernization · Sales Automation

To further support customers, JATO Dynamics wanted to create a reporting tool to offer car dealerships insights into their own performance compared to the market, including metrics like sales price, discount rates, and feature popularity.

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By automating content generation, Crow says, dealerships are saving approximately 32 hours each month, allowing them to allocate resources more efficiently.
In addition to Azure OpenAI, JATO Dynamics used Azure Cosmos DB to manage and store the data from millions of transactions across over 55 car brands.
Operating in more than 50 countries, JATO Dynamics collects data on car sales and trends to give customers a market view of the automotive industry.
With Sales Link, dealerships save around 32 hrs/mo.

Reported impact

Business outcome

With Sales Link, dealerships save around 32 hrs/mo.

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement
  • Revenue Growth

Solution

JATO Dynamics built this solution on Azure OpenAI Service, Azure AI Search, Azure Data Factory, Azure App Service. To further support customers, JATO Dynamics wanted to create a reporting tool to offer car dealerships insights into their own performance compared to the market, including metrics like sales price, discount rates, and feature popularity. Azure OpenAI Service provides the generative AI model layer used for summarization, drafting, classification, or copilots in the workflow. Azure AI Search indexes enterprise content so assistants and applications can retrieve grounded answers. Azure Data Factory moves and orchestrates data from source systems into the analytics platform. Azure App Service hosts the web application and API endpoints for the solution. JATO used the full Microsoft Azure stack, especially Azure OpenAI Service, to develop Sales Link. JATO Dynamics chose to use Microsoft Azure AI , specifically Azure OpenAI Service , to develop Sales Link.

Data flow

Operational data is ingested through Azure Data Factory from line-of-business systems, processed inside the analytics platform so business teams can act on a shared set of insights.

Solution architecture

6 components · 3 layers
  1. Ingest
    • Azure Data Factory Moves and orchestrates data from source systems into the analytics platform.
  2. Compute
    • Azure OpenAI Service Provides the generative AI model layer used for summarization, drafting, classification, or copilots in the workflow.
    • Azure App Service Hosts the web application and API endpoints for the solution.
    • Azure Functions Executes event-driven business logic inside automated workflows.
  3. Storage
    • Azure AI Search Indexes enterprise content so assistants and applications can retrieve grounded answers.
    • Azure SQL Database Stores transactional and reporting data that the application depends on.

Architecture clues

  • The solution is built around a governed cloud data foundation for shared analytics.

Evidence from the source

JATO used the full Microsoft Azure stack, especially Azure OpenAI Service, to develop Sales Link.
Operating in more than 50 countries, JATO Dynamics collects data on car sales and trends to give customers a market view of the automotive industry.
To further support customers, JATO Dynamics wanted to create a reporting tool to offer car dealerships insights into their own performance compared to the market, including metrics like sales price, discount rates, and f
With Sales Link, dealerships save around 32 hrs/mo.
With automated content generation, dealerships are saving approximately 32 hours each month.
Transparency Evidence & methodology 96/100 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 value96/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    3 metrics describe measurable impact.
  • Deployment scale10/10
    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
    5 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference 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

    JATO Dynamics customer story

    First-party
    https://www.microsoft.com/en/customers/story/19641-jato-dynamics-azure
    Source type
    Vendor-published customer story
    Published
    Nov 11, 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

Date evidence

  • Published on source page Nov 11, 2024 · Microsoft · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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