MicrosoftManufacturingEnterprise Knowledge SearchGenerative AI / LLMCost ReductionProductivity ImprovementRisk Reduction2024MicrosoftMS#0078d4ManufacturingFranceRoqGPT was born of one observation: employees' unbridled enthusiasm for ChatGPT. "The application quickly caught on with our employees. Within a few months, at least 500 of them had tested the online version," explains…A few months later, the chatbot was tested with a panel of 300 employees, before being extended to all Group…Mar 8, 20245Enterprise Knowledge SearchAzure OpenAI Service · Microsoft Azure · Microsoft Dynamics 36502024-03-085
RoqGPT was born of one observation: employees' unbridled enthusiasm for ChatGPT. "The application quickly caught on with our employees. Within a few months, at least 500 of them had tested the online version," explains Pierre-Louis Bescond, Head of Data & Advanced Analytics. This enthusiasm prompted the company to consider how to integrate this technology without compromising the high level of data confidentiality it has to comply with. "We wanted to avoid at all costs the disclosure or use of the questions asked via this tool to re-train future models,” adds Mathieu Klimczak, Lead DevOps in the Data & Advanced Analytics department.
↗A few months later, the chatbot was tested with a panel of 300 employees, before being extended to all Group entities worldwide.
Reported impact
Business outcome
"Our innovations are automatically accompanied by an increase in the autonomy and skills of our teams. It enables us to process this information in a secure environment, which is essential in our line of business." Making room for productivity, creativity, and people In just a short period of time, the number of users has passed the 1,000 mark, and millions of tokens—"digital assets"—are generated daily by the application.
Cost Reduction
Productivity Improvement
Risk Reduction
Solution
Roquette used Azure OpenAI Service, Microsoft Dynamics 365, Microsoft Azure to surface grounded answers from enterprise knowledge faster. RoqGPT was born of one observation: employees' unbridled enthusiasm for ChatGPT. "The application quickly caught on with our employees. Within a few months, at least 500 of them had tested the online version," explains Pierre-Louis Bescond, Head of Data & Advanced Analytics. This enthusiasm prompted the company to consider how to integrate this technology without compromising the high level of data confidentiality it has to comply with. "We wanted to avoid at all costs the disclosure or use of the questions asked via this tool to re-train future models,” adds Mathieu Klimczak, Lead DevOps in the Data & Advanced Analytics department. 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...
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
3 components · 2 layers
Compute
Azure OpenAI ServiceGenerates natural-language responses and task automation for the solution.
Microsoft AzureHosts the application, data, and integrations on scalable cloud infrastructure.
Orchestration
Microsoft Dynamics 365Provides the common business process layer that standardizes operations.
Architecture clues
Emphasizes secure enterprise access to data and AI capabilities.
Evidence from the source
"Our innovations are automatically accompanied by an increase in the autonomy and skills of our teams. It enables us to process this information in a secure environment, which is essential in our line of business." Making room for productivity, creativity, and people In just a short period of time, the number of users has passed the 1,000 mark, and millions of tokens—"digital assets"—are generated daily by the application.
A few months later, the chatbot was tested with a panel of 300 employees, before being extended to all Group entities worldwide.
At the same time, Microsoft launched Azure OpenAI Service .
RoqGPT was born of one observation: employees' unbridled enthusiasm for ChatGPT. "The application quickly caught on with our employees. Within a few months, at least 500 of them had tested the online version," explains Pierre-Louis Bescond, Head of Data & Advanced Analytics. This enthusiasm prompted the company to consider how to integrate this technology without compromising the high level of data confidentiality it has to comply with. "We wanted to avoid at all costs the disclosure or use of the questions asked via this tool to re-train future models,” adds Mathieu Klimczak, Lead DevOps in the Data & Advanced Analytics department.
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
4 direct source quotes retained.
Date provenance10/10
The publication date comes from the source page or publisher.
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