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PFAS Mitigation & Substitution App
Carbon Emissions AppSpeed in Compliance
PFAS Mitigation
Speed in Compliance
Overview
Overview
Challenges
Data required for PFAS mitigation is spread across the value chain in disparate silos
Material details required to perform assessment are with thousands of suppliers in many formats
Regulations & requirements are expanding with more imminent crackdowns and needs for disclosure
Challenges
Data required for PFAS mitigation is spread across the value chain in disparate silos
Material details required to perform assessment are with thousands of suppliers in many formats
Regulations & requirements are expanding with more imminent crackdowns and needs for disclosure
Viridium.AI Solution(s) Used
- Data mesh to automate collection of structured data across various lines of business
- Knowledge builders for data enrichment to fill in the blanks of critical missing information
- PFAS intelligent AI application, inclusive of 1-click reporting, to expedite access to critical PFAS impact analysis reports/insights for Supply Chain Ops and Compliance Managers.
Results
Results
Compliance Managers are now able to assess business impact in a matter of days vs months, for specific products. Supply Chain Ops can now easily stack rank suppliers based on PFAS impact and risk to take corrective action(s) (+productivity, + time-to-value)
This is great, innovative, and fills the need of a critical pain we’re experiencing.
Sr Exec, Global Supply Chain Operations,
Medical Device Manufacturer
This is great, innovative, and fills the need of a critical pain we’re experiencing.
Key Takeaways:
- Customer data (both structured and unstructured) was siloed, incomplete, and did not provide enough value back to key stakeholders despite massive investments in data infrastructure (ITOT/ERP/front and back office software)
- Internal data lacked enrichment from industry standards and framework
- Non-technical teams were unable to query and gain access to insights. This strategic approach laid the groundwork for strategic expansion and AI transformation
Speed in Compliance
Harnessing the Power of AI to Accelerate PFAS Mitigation
Overview
A leading medical device manufacturer, opera ng in over 100 countries with 60+ manufacturing facilities, faced the crucial task of mi ga ng PFAS from their products. This endeavor is not only existential but also critical for maintaining trust with internal and external stakeholders. However, the manual management of this process can extend beyond a month, significantly impacting productivity and expenses
Challenges
Data required for PFAS mitigation is spread across the value chain in disparate silos
Material details required to perform assessment are with thousands of suppliers in many formats
Regulations & requirements are expanding with more imminent crackdowns and needs for disclosure
Viridium.AI Solution(s) Used
- Data mesh to automate collection of structured data across various lines of business
- Knowledge builders for data enrichment to fill in the blanks of critical missing information
- PFAS intelligent AI application, inclusive of 1-click reporting, to expedite access to critical PFAS impact analysis reports/insights for Supply Chain Ops and Compliance Managers.
Results
Structured and unstructured data is now unified, in one platform, and layered with advanced AI, to make prompting and extracting insights simple (+productivity, +risk mitigation, +TCO)
Compliance Managers are now able to assess business impact in a matter of days vs months, for specific products. Supply Chain Ops can now easily stack rank suppliers based on PFAS impact and risk to take corrective action(s) (+productivity, + time-to-value)
This is great, innovative, and fills the need of a critical pain we’re experiencing. Lets do a pilot.
Sr Director, Global Opera1ons Manager,
Medical Device Manufacturer
Key takeaways
Viridium.AI’s platform solved 3 critical needs
- Customer data (both structured and unstructured) was siloed, incomplete, and did not provide enough value back to key stakeholders despite massive
- investments in data infrastructure (ITOT/ERP/front and back office software)
- Internal data lacked enrichment from industry standards and framework
- Non-technical teams were unable to query and gain access to insights. This strategic approach laid the groundwork for strategic expansion and AI transformation.