As commodity markets grow more interconnected, supply chains face rising complexity beyond trading desks. ETRMs manage core supply and operations, but logistics data fragments across shipping, trucking, rail, and storage systems, making coordination difficult. This lack of integration slows decisions and limits predictive analytics at scale. AI closes these gaps with automation, system upgrades, and intelligent workflows that improve speed, accuracy, and execution.

Value Creed supports this shift by optimizing supply and logistics processes, creating an avenue within the system landscape where AI/ML models can be implemented to remove operational friction and to provide superior operational advantage. With clean, connected data across systems, contracts, and infrastructure, organizations build the foundation AI needs to deliver measurable value.

Value Creed Services Powering AI-Ready Supply Chains

We identify AI use cases, define value benefits, and map hypotheses with decision trees to build a clear execution runway. This includes breaking down required technology stacks and consolidating them into an outcome-driven roadmap. Our approach leverages ETRM advisory to upgrade the core systems that power transaction lifecycle processing.

We deploy flexible ETRM platforms and extend them with external AI models connected through high-performance, low-latency APIs. Contracts, logistics, and inventory data flow into the model, with outputs returned for real-time recommendations and automated workflows. Our implementation approach emphasizes integration, visibility, and scalability, creating the backbone for AI-driven supply chains.

We guide firms in selecting the right ETRM systems and features to enable an AI-first culture. This includes introducing accelerators, identifying high-impact features, and right-sizing infrastructure to support a hybrid ecosystem where AI/ML models seamlessly enhance core processes.

We move from strategy to execution by cutting across data engineering, model development, ETRM customization, and advanced monitoring. Our teams deliver hands-on build and run capabilities in a hybrid environment where AI/ML models work seamlessly with business processes. From pipeline automation and model deployment to observability and performance monitoring, we ensure insights translate into reliable, day-to-day outcomes.

Transforming Supply Chain Challenges into AI-Driven Strengths

Unified Supply Chain Visibility

ETRMs handle contracts, nominations, and scheduling, but logistics often run on separate maritime, trucking, and rail systems. This fragmentation slows coordination and limits visibility. AI unifies real-time data, reducing blind spots and improving decisions, with models like Random Forest reconciling fragmented datasets.

Automated Workflow Acceleration

Manual tasks like contract validation,
BOL handling, and invoice reconciliation cause delays and errors.
AI automation streamlines these workflows for straight-through processing, while predictive models like SVMs detect anomalies early to prevent breakdowns.

Dynamic Predictive Forecasting

Supply and logistics decisions are often reactive, missing early warning signals from disruptions such as port congestion, rail bottlenecks, or geopolitical risks. AI models like XGBoostprocess these signals in real time, allowing proactive rerouting, dynamic scheduling, and sourcing adjustments that improve operational resilience.

AI-Optimized Logistics Planning

Once commodity flows move beyond ETRM systems, routing decisions often lack integration of key inputs such as vessel delays, trucking constraints, or fluctuating fuel costs. Predictive logistics powered by AI consolidates these variables, improving planning precision, delivery reliability, and cost efficiency.

Self-Learning Scalability

As supply networks evolve with new fleets, assets, or partners, traditional algorithms struggle to adapt. AI models self-adjust to these changes, eliminating the need to re-run regressions. This reduces interpretation time and allows operations to scale seamlessly without added complexity.

Value Creed Fuels Efficiency through Process Automation for a Premier Fuel Supplier

75% Operational Efficiency through Process Automation for a Premier Fuel Supplier

Case Study

Automating Logistics for Performance at Scale

Value Creed collaborated with a premier North American fuel supplier to transform
error-prone logistics with process automation. By digitizing Bill of Lading validation and streamlining data across systems like RightAngle, we reduced manual analysis time by 75% and improved BOL data accuracy to 95%.

Staying Ahead with AI-Enhanced Supply Chains

Artificial Intelligence is emerging as a defining capability for commodity trading firms working to simplify complexity across supply, operations, and logistics. By integrating data across multiple systems, eliminating manual bottlenecks, and powering predictive insights, AI transforms challenges into opportunities for speed, precision, and resilience. With advances like multimodal and agentic AI, models are becoming more adaptive and capable of managing interconnected workflows with greater intelligence. From optimizing IT processes to shaping long-term investment strategies, the ability to scale intelligence across the supply chain is quickly becoming a competitive edge.

Value Creed enables this transformation by delivering the expertise, services, and technology foundations required to make AI adoption practical and effective. With advisory, implementation, and expertise-on-demand services, we help firms turn AI potential into measurable value. Empowering supply chains to operate with confidence, agility, and next-level intelligence.

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Driving Supply Chain Efficiency in Commodity Trading with Artificial Intelligence

Redefining Supply Chain Efficiency with AI in Commodity Trading

Value Creed Services Powering AI-Ready Supply Chains

Transforming Supply Chain Challenges into AI-Driven Strengths

Unified Supply Chain Visibility

Automated Workflow Acceleration

Dynamic Predictive Forecasting

AI-Optimized Logistics Planning

Self-Learning Scalability

Automating Logistics for Performance at Scale

Staying Ahead with AI-Enhanced Supply Chains

Recommended Resources

Ready to get started?