
Introduction
IDEWE, Belgium's leading external service for workplace prevention and protection, has one clear mission: improve the well-being of employees and workplace environments.
Client
IDEWE
Client since
2023
Solutions
Technologies
The problem
With over 35,000 clients and a mountain of unstructured data to manage, from occupational health to IoT devices and governance frameworks, IDEWE faced a massive challenge:
How do you make all this data actually work?
How we solved it
Structure in the Chaos
Much of IDEWE's valuable information was hidden in unstructured free text, making it hard to extract, aggregate, or share insights. We standardized their data at the source, transforming vague narratives into structured, actionable formats. With proper categorization and strict access controls in place, data could finally flow securely, only to those who needed it.
Streaming IoT for Real-Time Action
For vaccination storage and other critical use cases, IDEWE needed more than historical insights, they needed data in the now. We built a streaming architecture on Azure IoT Hub, enabling real-time monitoring and alerts. What started with refrigerators evolved into a blueprint for future IoT applications, like wearables for personal health tracking.
Compliance-Driven, Business-Ready Governance
ISO27001 wasn't a box-ticking exercise, it was an opportunity to build real trust in data. We implemented Microsoft Purview for end-to-end governance, integrated technical lineage via Sparklin, and embedded continuous quality checks with Validio. Result? IDEWE now has full confidence in their data's origin, quality, and compliance.
Smarter Communication with AI
We even brought data accessibility to the next level with a chatbot POC that interacts with validated internal data. Designed with IDEWE's branding and governance standards in mind, this LLM-powered assistant helps employees get instant, reliable answers boosting productivity without compromising data accuracy.
Structure in the Chaos
Much of IDEWE's valuable information was hidden in unstructured free text, making it hard to extract, aggregate, or share insights. We standardized their data at the source, transforming vague narratives into structured, actionable formats. With proper categorization and strict access controls in place, data could finally flow securely, only to those who needed it.
Streaming IoT for Real-Time Action
For vaccination storage and other critical use cases, IDEWE needed more than historical insights, they needed data in the now. We built a streaming architecture on Azure IoT Hub, enabling real-time monitoring and alerts. What started with refrigerators evolved into a blueprint for future IoT applications, like wearables for personal health tracking.
Compliance-Driven, Business-Ready Governance
ISO27001 wasn't a box-ticking exercise, it was an opportunity to build real trust in data. We implemented Microsoft Purview for end-to-end governance, integrated technical lineage via Sparklin, and embedded continuous quality checks with Validio. Result? IDEWE now has full confidence in their data's origin, quality, and compliance.
Smarter Communication with AI
We even brought data accessibility to the next level with a chatbot POC that interacts with validated internal data. Designed with IDEWE's branding and governance standards in mind, this LLM-powered assistant helps employees get instant, reliable answers boosting productivity without compromising data accuracy.
The results
A Company That Doesn't Just Collect Data, It Uses It.
IDEWE now operates with better insight, faster decisions, and full trust in its data systems. With future-proof infrastructure in place, they're equipped for everything from proactive health tracking to smart internal tools powered by AI.
100%
of pilot users recommend the AI assistant
95%
of pilot users will keep using the AI assistant
85%
of pilot users work more efficient with the AI assistant
Key Learnings
Don't wait
Ship early (even a simple Streamlit prototype for the first test-users), and observe how people actually use it, and continously refine it using real-world conversations instead of assumptions. Treat data quality as part of the chatbot project.
Learn and improve along the way
Make it a two-sided initiative where the rollout of the chatbot goes hand in hand with improving the quality and structure of the underlying (unstructured) data.
Invest in your users
Invest in user training and clear expectation setting. Explain what the chatbot can and cannot do, so users know how to use it effectively. This built trust and improves adoption.
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