Pillar leverages advanced artificial intelligence to unlock the hidden value in your supply chain data, transforming how you approach planning and decision-making.
Key Features
Probabilistic Framework
We treat every transaction in your supply chain as a random variable, from shipments and production statements to demand forecasts.
Our AI models are trained on your entire business ecosystem, creating a comprehensive simulation that culminates in an overall business Lost Sales curve.
This bottom-up approach allows for granular analysis at every step of the process, providing unprecedented insight into your supply chain dynamics.
Probabilistic Forecasting
Demand Forecasting: We go beyond traditional time-series forecasting, considering all possible future scenarios and their probabilities for more nuanced risk assessment and decision-making.
Supply Forecasting: Every element of your supply chain is modeled probabilistically, from shipment arrivals to order completeness, providing a comprehensive understanding of underlying risks and potential outcomes.
Stochastic Optimization
Pillar AI employs advanced stochastic optimization techniques to make risk-adjusted decisions in the face of uncertainty.
Our system balances multiple factors and constraints simultaneously, ensuring robust solutions that align with your risk preferences and business objectives.
Financial Optimization
Our platform optimizes supply chain decisions based on financial impact, expressed in monetary terms.
We focus on maximizing return on investment rather than adhering to arbitrary KPIs or percentages, ensuring that every decision contributes directly to your bottom line.
Intelligent Data Lake
We create a unified data model that ingests and harmonizes data from various sources, including ERP systems, supply chain management tools, and EDI messages.
Our AI-powered system uses machine learning and natural language processing to map and transform data from diverse sources into a standardized format, providing a single source of truth for your supply chain operations.
Comprehensive Economic Drivers
Our optimization process incorporates a wide range of economic factors, including both direct (e.g., gross margin, shipping costs) and indirect (e.g., customer goodwill, brand perception) drivers.
This holistic approach ensures that all relevant factors are considered in the decision-making process, leading to more balanced and effective outcomes.
Automated Decision-Making
While we provide detailed recommendations, our platform emphasizes fully automated decision-making for routine supply chain tasks, reducing the need for manual intervention.
This automation frees up your team to focus on strategic initiatives and complex problem-solving, enhancing overall efficiency.
Proactive Problem Solving
Instead of relying on reactive alerts, our AI continuously adjusts its algorithms to prevent issues before they occur.
This forward-thinking approach minimizes disruptions and helps maintain a smooth, efficient supply chain operation.
Unified Dashboard
We provide a single, comprehensive dashboard for each corporate function, prioritizing tasks based on monetary impact.
This approach streamlines decision-making and ensures focus on the most critical issues, improving overall supply chain performance.
Transparent Decision Rationale
For every recommendation, Pillar AI provides detailed explanations, breaking down the economic factors influencing each choice.
This transparency builds trust in the system and aids in continuous improvement of your supply chain strategies.
Continuous Learning and Improvement
Our AI models continuously learn from changing patterns and user inputs, offering near real-time updates to forecasts and recommendations.
This adaptive approach ensures that your supply chain planning remains agile and responsive to market changes and emerging trends.