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Mercedes-Benz Group

Document Processing · Enterprise Knowledge Search

Mercedes-Benz needed a secure, compliant internal generative AI tool that could simplify daily knowledge work, provide fast context-aware answers, and support cross-functional collaboration without exposing personal or sensitive data.

More than 10,000 employees use Direct Chat daily as power users.
One concrete example is our AI Learning Journey, which tens of thousands of colleagues have already completed.

Reported impact

Business outcome

Direct Chat became an established internal AI platform across the organization, giving employees reliable support for writing emails and reports, summarizing documents, accessing internal knowledge, and collaborating across international teams in a secure and compliant environment.

  • Compliance
  • Productivity Improvement

Solution

Mercedes-Benz Group built Mercedes-Benz Direct Chat as an internal web application for enterprise generative AI use. Employees submit prompts through the Direct Chat interface, which was originally based on OpenAI's ChatGPT technology and is integrated through Microsoft Azure OpenAI Service. This gives the company a managed environment for running LLM workloads with Azure security, privacy, and reliability controls. In 2025, Mercedes-Benz added Google Gemini so users can choose between multiple AI models, and it added DALL.E for image generation and image analysis inside the same experience. Mercedes-specific knowledge agents connect the chat experience to internal systems so the application can return tailored answers from company content and act as a central information platform. The solution is served in English and German, hosted in European data centers, processes employee prompts anonymously, and is governed by internal data protection policies and AI usage guidelines rather than storing sensitive data for model training.

Data flow

Employees enter prompts in Mercedes-Benz Direct Chat, which routes requests through Microsoft Azure OpenAI Service to ChatGPT or Gemini, with DALL.E handling image generation and analysis tasks. Mercedes-specific knowledge agents retrieve relevant context from internal systems and return tailored answers in the same chat interface. Inputs are processed anonymously, and operations are hosted in European data centers.

Solution architecture

6 components · 4 layers
  1. Compute
    • ChatGPT It provides the core large language model capability that powers fast, context-aware text responses.
    • Google Gemini It adds an additional AI model option so employees can use multiple models depending on their needs.
    • DALL.E It enables image generation and image analysis directly within the chat workflow.
  2. Serving
    • Mercedes-Benz Direct Chat The internal web application provides employees with a single chat interface for writing, summarization, image tasks, and access to company knowledge.
  3. Orchestration
    • Mercedes-specific knowledge agents They pull tailored insights from internal systems and inject company-specific context into responses.
  4. Uncategorized
    • Microsoft Azure OpenAI Service It is the managed integration layer Mercedes-Benz uses to run the generative AI service with Azure security, privacy, and reliability controls.

Architecture clues

  • All operations are hosted in European data centers.
  • Available in both English and German.
  • Employee text inputs are processed anonymously.
  • Employees are instructed not to enter personalised or internal data and to review AI-generated content before use.
  • Mercedes-Benz retains full control over the underlying IT processes.
  • No personal or sensitive data is stored or used to train AI models.
  • Originally launched in late 2023.
  • Updated in August 2025 to add Google Gemini and DALL.E features.

Evidence from the source

"All operations are hosted in European data centers, with Mercedes-Benz retaining full control over the underlying IT processes."
"Employee text inputs are processed anonymously, and no personal or sensitive data is stored or used to train AI models."
"Mercedes-specific knowledge agents provide tailored insights from internal systems, making Direct Chat the central information platform for internal content and cross-functional collaboration."
"More than 10,000 employees use Direct Chat daily as power users."
"New features such as image generation and analysis using DALL.E are now also available directly within the chat."
"One of the tools the company relies on to simplify daily processes and boost efficiency is the Mercedes-Benz Direct Chat."
"The application is integrated via the Microsoft Azure OpenAI Service, combining the power of large-scale generative AI with Azure’s robust security, privacy and reliability features."
"This AI-powered chatbot is based on OpenAI’s ChatGPT technology and delivers precise, context-aware responses within seconds."
"With its latest update in August 2025, Direct Chat has become even more powerful – thanks to the integration of Google Gemini, employees now have access to multiple AI models depending on their needs."
Transparency Evidence & methodology 71/100 reference value · 92% 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 confidence92%
  • Source authority25/25
    The deployment is described by the adopting organization or a government source.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    9 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. Mercedes-Benz Group

    Mercedes-Benz Group customer story

    First-party
    https://group.mercedes-benz.com/technology/digitalisation/artificial-intelligence/mercedes-benz-direct-chat.html
    Source type
    Customer-published story
    Published
    Oct 6, 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

  • Published on source page Oct 6, 2025 · Mercedes-Benz Group · 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.