Microsoft Manufacturing Belgium

Syensqo

Enterprise Knowledge Search

Syensqo, a Belgian science and technology powerhouse, faced challenges in managing and utilizing vast amounts of internal data efficiently. The company needed a robust, secure, and scalable AI solution to enhance data access and operational efficiency. The existing systems were not capable of meeting these demands, leading to inefficiencies and delays in their operation.

Reported impact

Business outcome

This comprehensive solution enabled Syensqo to enhance their data processing capabilities and improve overall efficiency. They experienced improved data processing efficiency, leading to faster decision-making and reduced operational delays.

  • Customer Experience
  • Productivity Improvement
  • Risk Reduction
  • Speed to Market

Solution

Syensqo used Azure OpenAI Service, Microsoft Dynamics 365, Azure Cosmos DB to surface grounded answers from enterprise knowledge faster. Syensqo, a Belgian science and technology powerhouse, faced challenges in managing and utilizing vast amounts of internal data efficiently. The company needed a robust, secure, and scalable AI solution to enhance data access and operational efficiency. The existing systems were not capable of meeting these demands, leading to inefficiencies and delays in their operation. Key implementation elements included Azure OpenAI Service generates natural-language responses and task automation for the solution; Microsoft Dynamics 365 provides the common business process layer that standardizes operations; Azure Cosmos DB stores application state and knowledge or interaction data; Azure API Management governs the APIs that connect the platform to other systems. Enterprise content from documents, meetings, websites, or internal systems is passed through...

Data flow

Enterprise content from documents, meetings, websites, or internal systems is passed through retrieval and model services so users receive grounded answers inside the target workflow.

Solution architecture

5 components · 4 layers
  1. Compute
    • Azure OpenAI Service Generates natural-language responses and task automation for the solution.
    • Microsoft Azure Hosts the application, data, and integrations on scalable cloud infrastructure.
  2. Storage
    • Azure Cosmos DB Stores application state and knowledge or interaction data.
  3. Orchestration
    • Microsoft Dynamics 365 Provides the common business process layer that standardizes operations.
  4. Uncategorized
    • Azure API Management Governs the APIs that connect the platform to other systems.

Architecture clues

  • Emphasizes secure enterprise access to data and AI capabilities.

Evidence from the source

Syensqo chose to implement Microsoft's Azure OpenAI Service to address their challenges.
Syensqo, a Belgian science and technology powerhouse, faced challenges in managing and utilizing vast amounts of internal data efficiently. The company needed a robust, secure, and scalable AI solution to enhance data access and operational efficiency. The existing systems were not capable of meeting these demands, leading to inefficiencies and delays in their operation.
Syensqo.AI, a division started only six months ago by the Belgian science and technology powerhouse Syensqo, has developed SyGPT, an advanced AI chatbot powered by Azure OpenAI Service.
The Azure OpenAI Service offered advanced capabilities, including GPT models for natural language processing, Cosmos DB for data management, and API Management for seamless integration with other systems.
This comprehensive solution enabled Syensqo to enhance their data processing capabilities and improve overall efficiency. They experienced improved data processing efficiency, leading to faster decision-making and reduced operational delays.
Transparency Evidence & methodology 70/100 reference value · 90% 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 confidence90%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • 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

    Syensqo customer story

    First-party
    https://www.microsoft.com/en/customers/story/18989-syensqo-azure-open-ai-service
    Source type
    Vendor-published customer story
    Published
    Oct 10, 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. Syensqo

    About Syensqo | Syensqo

    First-party
    https://www.syensqo.com/en/about-us

    With a diverse global team of more than 13,000 employees in 30 countries, we work together to advance science and help humanity move forward.

    Source type
    Official company website
    Supports
    • Company size

Date evidence

  • Published on source page Oct 10, 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.