01 Business signals
Start with the operating reality.
Bring orders, capacity, stock and business rules into one defined decision context. Check what is known, what is missing and who owns the data.
Orderbook · capacity · stock
From business priorities to operational decisions.
We combine advisory work, decision science and engineering around a specific business workflow. Each engagement starts with accountable owners, operational constraints and an agreed measurement baseline.
Operations & production alignment
Connect order commitments, dynamic costs and finite capacity to make production plans that reflect real operating constraints.
- The management question
- Which orders should we accept, at what margin, and with which delivery commitments when capacity is constrained?
- What we deliver
- An OmniSolve order–cost–schedule model, ATP/CTP scenarios and a capacity-feasible plan with explanations of binding constraints.
- How value is measured
- On-time delivery · contribution margin · schedule adherence · capacity utilization
Supply chain & procurement resilience
Balance service levels, inventory and supply risk across procurement, replenishment and allocation decisions.
- The management question
- How much inventory should each location hold, and how should sourcing change when demand or lead times become uncertain?
- What we deliver
- Multi-echelon inventory policies, supplier lead-time scenarios, replenishment recommendations and disruption alternatives.
- How value is measured
- Fill rate · inventory days · stockouts · procurement cost · recovery time
Energy & low-carbon operations
Coordinate energy assets, demand and commercial constraints within a shared energy–carbon–finance model.
- The management question
- How should storage, on-site generation and flexible demand operate as prices, carbon objectives and asset limits change?
- What we deliver
- Dispatch and demand-response scenarios, storage operating policies and investment sensitivities with explicit assumptions.
- How value is measured
- Energy cost · peak demand · emissions · asset degradation · project cash flow
Cash flow & working capital
Bring finance and operations onto the same view of liquidity, inventory, receivables and payment timing.
- The management question
- Which operating choices protect liquidity without weakening fulfillment or supplier relationships?
- What we deliver
- Rolling liquidity scenarios, AR/AP and inventory trade-offs, cash-conversion-cycle analysis and risk sensitivities.
- How value is measured
- Cash conversion cycle · liquidity buffer · forecast error · overdue receivables
Enterprise AI & decision governance
Move from an AI experiment to a governed workflow, with private deployment, human approvals and traceable execution.
- The management question
- Which decisions can AI support, who remains accountable, and what must be explained before a recommendation is executed?
- What we deliver
- A use-case assessment, decision model, deployment design, approval rules and an auditable recommendation-to-execution workflow.
- How value is measured
- Decision cycle time · approval adherence · traceability · operational exceptions
Data governance & lakehouse foundations
Build the data foundation for enterprise decisions. AEVO connects governance, data lakes and Medallion pipelines to analytics, AI and decision optimization.
- The management question
- Can teams reconcile orders, stock and capacity across systems, trust their freshness and explain which records informed a decision?
- What we deliver
- A scoped governance model, source inventory, Bronze/Silver/Gold pipelines, documented data products and a reviewed interface to the Decision Engine.
- How value is measured
- Freshness against agreed limits · reconciliation exceptions · lineage coverage · pipeline recovery · decision-input readiness
THE DECISION JOURNEY
From signals to accountable action.
A forecast becomes useful when it meets real constraints, reveals the trade-offs, and gives people a decision they can review.
02 ML forecast
Understand what may change.
Forecasts describe possible demand and uncertainty. They inform the decision; a predicted number alone does not choose the operating plan.
Expected demand · uncertainty range
03 OR & constraints
Compare what is feasible.
Evaluate alternatives against capacity, availability, service and budget constraints. Make the cost of each trade-off visible before choosing a plan.
Feasible plans · explicit trade-offs
04 Explanation
Show the reasoning behind the plan.
Connect the recommendation to its inputs, assumptions and binding constraints. The team should be able to understand what would change the recommendation.
Rationale · assumptions · alternatives
05 Human review
Keep responsibility with people.
Route the proposed plan to the responsible team, record approval or changes, and follow its outcomes. Human review remains part of the decision process.
Decision owner · approval · follow-up
Illustrative workflow · synthetic inputs · Conceptual illustration of the workflow. No customer results or live AI inference are shown.
Our approach
A disciplined path from insight to execution.
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Frame the decision
Agree on business owners, data boundaries, constraints and the current performance baseline.
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Validate in shadow mode
Compare model recommendations against existing decisions before changing live operations.
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Integrate with control
Connect agreed systems, approval gates and exception handling with your operating teams.
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Monitor value over time
Track agreed KPIs, review model behavior and adapt as business conditions change.
Start with a decision that matters.
Tell us where cost, capacity, risk or cash is limiting performance. We will help define a focused evaluation before committing to a wider transformation.