John Galt Solutions expands Atlas Planning Platform’s explainable AI to build trust in supply chain decisions 

John Galt Solutions, the fastest way to achieve more value from the supply chain, announced newly enhanced explainable AI capabilities in its market-leading Atlas Planning Platform. By leveraging Generative AI (GenAI) to provide transparency and context, Atlas empowers supply chain organizations to understand, trust, and act on AI-driven insights with speed and confidence.

For many companies, AI in supply chain planning has long been associated as “black box” systems – technologies that deliver recommendations without the context and reasoning behind recommendations or understanding of the complex algorithms that provided them. This lack of explainability has slowed adoption of advanced processes such as Multi-Echelon Inventory Optimization (MEIO) and Ensemble forecasting, leaving teams unable to fully unlock the value of these powerful approaches. The latest enhancements in the Atlas Planning Platform change that by combining advanced analytics with explainable AI (xAI), to democratize access to insights and accelerate decision-making.

“At John Galt Solutions, we’re focused on demystifying AI so that it is intuitive, transparent, and empowering” – said Matt Hoffman, vice president of product and industry solutions at John Galt Solutions. “With our further developments in explainable AI, Atlas delivers powerful recommendations while also providing the context behind them. This builds trust, accelerates adoption, and allows planners to make confident decisions that add significant value.”

Unlocking MEIO Value

Multi-Echelon Inventory Optimization is one of the most impactful yet underutilized capabilities in supply chain planning. MEIO delivers tremendous value, helping companies balance inventory across multi-node networks to free up working capital while simultaneously improving service levels. However, many businesses have been hesitant to embrace the process because of the complexity involved to optimize inventory from finished goods to raw materials across each location in the network.

Galt Intelligence – Atlas’ GenAI assistant – makes MEIO highly approachable, understandable and actionable. Atlas’ intuitive, conversational interface transforms confusing stacks of data by explaining where and why inventory changes are recommended, identifying risk-pooling opportunities, and highlighting the value delivered. This enables planners to trust and act on optimization results while being fully in control of the process.

Building Confidence in Ensemble Forecasting

Ensemble forecasting brings together multiple models to identify the best possible prediction. While highly effective, the process can leave planners questioning why certain forecasts are prioritized over others, especially when models show different peaks and valleys.

Atlas solves this challenge by applying GenAI explainability to reveal the logic behind ensemble outcomes, clarifying why particular patterns, trends, or models were selected and how the combined forecast improves accuracy. This clarity ensures that planners understand the forecast’s elements and trade-offs to have the confidence to act quickly.

“With intuitive analytics, intelligent workflows, advanced automation, and data contextualization, Atlas provides fast time-to-value while keeping humans firmly in the loop,” said Hoffman.

Democratizing AI for Supply Chains

The expanded explainability features in the Atlas Planning Platform reinforce John Galt Solutions’ mission to democratize AI for supply chains, delivering the right recommendations along with the clarity and confidence for supply chain teams to act on them.

Through contextual insights and guided decision-making, Atlas enables planners to trust AI-driven recommendations without sacrificing human judgment. This leads to stronger adoption and usability, as well as enhanced alignment across the end-to-end supply chain and better business outcomes.