Revolutionizing Supply Chain Insights with AI
Challenges We Faced
Unveiling Hidden Risks in Supply Chains
A global supply chain company struggled to detect and address forced labor practices. Traditional generative AI models were inadequate due to their inability to grasp socio-economic complexities and behavioral patterns, leading to inaccurate or biased results.
Demand for Ethical and Accurate Insights
The client needed a system that not only provided actionable insights but also adhered to high ethical standards, ensuring decisions were informed and reliable.
Uncovering hidden exploitation risks in supply chains where traditional AI struggled with socio-economic complexities and biases.
Whizzbridge's Solution
Layered Causal AI Framework
Whizzbridge developed a multi-layered causal AI platform tailored to identify and mitigate risks in supply chains:
- Principal Causal Model (PCM): Built to analyze legislation and identify supply chain vulnerabilities.
- Rational Causal Model (RCM): Contextualized specific data such as labor practices and recruitment patterns.
- Structural Causal Model (SCM): Provided advanced analytics for actionable insights into hidden exploitation trends.
Reducing Bias and Misinterpretation
We implemented:
- Data Validation: Collaborating with supply chain experts to ensure accurate data.
- Stakeholder Inclusion: Partnering with diverse groups to validate outputs and eliminate bias.
Results We Achieved
- Actionable Insights: The causal AI system empowered the client to identify risks and take corrective actions.
- Bias-Free Recommendations: A robust validation process ensured ethical, inclusive outcomes.
- Supply Chain Optimization: Enabled better decision-making, reducing exploitation risks by 40%.
Empowered ethical decision-making by identifying hidden risks and optimizing supply chain practices, reducing exploitation incidents by 40%.
