AEVO builds private AI, machine learning, and Operations Research systems for demand forecasting, inventory, supply chain, energy trading, cash flow, and portfolio risk.
AEVO works alongside ERP, MES, WMS, finance, and energy systems so customer-specific models can run privately without disrupting current operations.
A compact board-ready view of how seven linked layers move from private enterprise data to governed execution, with a closed feedback loop across the full stack.
Each layer informs the next. Each execution outcome strengthens the layers below it.
AEVO applies AI, machine learning, and Operations Research to the decision surfaces that shape service, resilience, carbon exposure, and free cash flow.
Workforce and service-level control
Use labor as an operating lever instead of a scheduling afterthought.
Balance staffing, service levels, labor policy, and volatility in one scheduling workflow that managers can actually operate day to day.
Supply and inventory resilience
Make inventory and sourcing decisions with risk, cash, and service commitments visible together.
Reduce excess stock without surrendering service levels by turning supplier risk, demand uncertainty, and capital pressure into one governed decision model.
Support sourcing teams with a decision framework that connects supplier signals, price trajectories, and negotiation leverage before the next purchasing cycle.
Energy and facility orchestration
Treat distributed assets, building loads, and carbon pressure as one dispatch problem.
Coordinate generation, storage, and site-level demand so operators can act on price, carbon, and reliability trade-offs in one place.
Liquidity and capital protection
Support treasury and finance teams with decisions that stay close to policy and far from black-box guesswork.
Make collections, payables, and capital efficiency visible as one operating decision instead of a disconnected set of finance interventions.
Give treasury teams scenario-ready liquidity views that are actionable enough to support hedging, cash positioning, and policy-aware escalation.
The first project should create operational proof, not organizational drag.
We prioritize workflows where a better decision changes cash, service, throughput, or risk quickly enough to matter.
Approval logic, policy boundaries, and auditability are treated as product requirements rather than post-launch controls.
Once the operating pattern works, the same AEVO layer can support adjacent decisions across the organization.
We build systems for demand forecasting, inventory, supply chain, carbon and energy trading, working capital, and portfolio risk instead of generic AI demos.
We analyze customer data, build custom algorithms and models, and use their dynamic interaction to improve free cash flow, resilience, and capital efficiency.
AEVO adds a governed decision layer on top of your existing stack so teams can adopt advanced models without disrupting ERP, MES, WMS, finance, or operational workflows.
We can help define the first high-value workflow, the right data and deployment boundary, and the free-cash-flow proof points worth tracking.
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