Microsoft Automotive Sweden

Volvo Group

Document Processing

Known for its innovation in support of both employees and customers, Volvo Group, a leading manufacturer of trucks, buses, construction equipment, and industrial engines, wanted to help its workers by streamlining invoice and claims document processing.

Reported impact

Business outcome

Pushpalatha agrees, “We know this directly impacts the relationships between Volvo Group divisions and customers. When people are more satisfied with their work, it creates a better experience for everyone.”

  • Customer Experience
  • Productivity Improvement

Solution

Known for its innovation in support of both employees and customers, Volvo Group, a leading manufacturer of trucks, buses, construction equipment, and industrial engines, wanted to help its workers by streamlining invoice and claims document processing. It particularly needed the ability to extract data from images, like photographs and stamps, and to translate documents from and to multiple languages. With Microsoft Azure as its enterprise cloud solution, Volvo Group chose to create a solution using Microsoft Azure AI services and AI Document Intelligence. After a six-week pilot and four-month production timeline, Volvo Group launched a solution that simplifies document processing and meets the objectives of data extraction from images and translation. Now the solution has saved Volvo Group more than 10,000 manual hours. “We chose Microsoft Azure AI primarily because of the advanced capabilities offered, especially with AI Document Intelligence.”

Data flow

Documents arrive through Outlook, Azure Data Factory preprocesses scans, AI Document Intelligence and Azure AI services extract and translate the content, and Power Automate routes outputs to the right teams while Power BI tracks throughput and success metrics.

Solution architecture

5 components · 3 layers
  1. Compute
    • Azure AI Services Provides managed AI services for document understanding, translation, and other model-driven tasks.
    • AI Document Intelligence Extracts structured data from complex documents, including images, stamps, and tables.
  2. Serving
    • Power BI Publishes dashboards and reports so teams can track trends, KPIs, and operational status.
  3. Orchestration
    • Power Automate Automates approval, routing, and integration steps between operational systems.
    • Azure Data Factory Preprocesses and transforms inbound documents before extraction and routing.

Architecture clues

  • Documents arrive through Outlook, Azure Data Factory preprocesses scans, AI Document Intelligence and Azure AI services extract and translate the content, and Power Automate routes outputs to the right teams while Power BI tracks throughput and success metrics.
  • Known for its innovation in support of both employees and customers, Volvo Group, a leading manufacturer of trucks, buses, construction equipment, and industrial engines, wanted to help its workers by streamlining invoice and claims document processing. It particularly needed the ability to extract data from images, like photographs and stamps, and to translate documents from and to multiple languages. With Microsoft Azure as its enterprise cloud solution, Volvo Group chose to create a solution using Microsoft Azure AI services and AI Document Intelligence. After a six-week pilot and four-month production timeline, Volvo Group launched a solution that simplifies document processing and meets the objectives of data extraction from images and translation. Now the solution has saved Volvo Group more than 10,000 manual hours.
  • Volvo Group wanted a flexible platform solution that could evolve with Microsoft Azure AI services and other Microsoft technologies like Azure AI Document Intelligence. “We needed advanced capabilities, especially with AI Document Intelligence, to help us create a solution that extracts data from images—including photographs, stamps, and seals—and overwritten text to gain more detailed information about the products or services accounted for in the documents,” says Datta. “A technology which could quickly produce accurate text in multiple languages.”
  • “We chose Microsoft Azure AI primarily because of the advanced capabilities offered, especially with AI Document Intelligence.”

Evidence from the source

Known for its innovation in support of both employees and customers, Volvo Group, a leading manufacturer of trucks, buses, construction equipment, and industrial engines, wanted to help its workers by streamlining invoice and claims document processing. It particularly needed the ability to extract data from images, like photographs and stamps, and to translate documents from and to multiple languages. With Microsoft Azure as its enterprise cloud solution, Volvo Group chose to create a solution using Microsoft Azure AI services and AI Document Intelligence. After a six-week pilot and four-month production timeline, Volvo Group launched a solution that simplifies document processing and meets the objectives of data extraction from images and translation. Now the solution has saved Volvo Group more than 10,000 manual hours.
Volvo Group also employed Power Automate to create a data table in SharePoint detailing processing times for each document. The data was then linked to a Power BI report to track metrics such as average processing time, throughput time, and success rate of the automation. “The Azure solution gives us a lot of flexibility to innovate,” says Datta.
“The documents are received through Microsoft Outlook, and we use Power Automate cloud connector for Office 365 to copy, for example, a particular PDF file,” says Pushpalatha. “Using Azure Data Factory, we can preprocess documents to remove noise from scanned images, rotate and sequence images, and trim unnecessary pages. The output is either an XML or CSV file, depending on the Volvo Group division it will be sent to.” After the automation lifecycle, files are removed from storage and archived in a designated system.
Transparency Evidence & methodology 71/100 reference value · 82% 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 value71/100
  • 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 impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence82%
  • 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 evidence15/20
    3 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

    Volvo Group customer story

    First-party
    https://www.microsoft.com/en/customers/story/1703814256939529124-volvo-group-automotive-azure-ai-services
    Source type
    Vendor-published customer story
    Published
    Nov 16, 2023
    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 16, 2023 · 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.