Supply Chain

AI that sees disruptions coming and keeps your supply chain moving.

Visibility, planning, exception management.

Supply chain AI must operate on incomplete, delayed, and sometimes deliberately misleading data from suppliers, carriers, and customs. We've built visibility and planning systems that work in this reality — surfacing the signal in the noise before it becomes a line-stop.

Use cases

Supply disruption detection

Multi-signal monitoring (news, shipping data, supplier capacity, geopolitical risk) that flags supply threats 2–4 weeks before they become shortages.

Demand-supply matching

AI-driven allocation optimization when supply is constrained — prioritizing customers, channels, and SKUs by margin, relationship, and contract terms.

Inventory optimization

SKU-location-level safety stock modeling that reduces carrying cost without increasing stockout risk — calibrated to your service level targets.

Supplier risk scoring

Continuous supplier health monitoring incorporating financial, operational, and reputational signals with configurable alert thresholds.

Customs & trade intelligence

Automated HS code classification, duty optimization, and trade compliance monitoring across your import/export portfolio.

S&OP AI copilot

AI support for Sales & Operations Planning that surfaces data conflicts, models scenarios, and documents decision rationale for executive review.

Why Evolve Edge

Multi-tier visibility Our systems aggregate data from Tier 1, Tier 2, and Tier 3 suppliers — surfacing disruption risk upstream before it hits your production schedule.

Probabilistic planning Supply chain planning that quantifies uncertainty rather than pretending it doesn't exist. Risk-adjusted plans, not deterministic projections that are wrong by day 3.

Action-oriented intelligence AI that doesn't just flag a problem — it suggests the alternative sourcing option, the safety stock adjustment, or the customer communication that needs to go out now.

Evolve Edge team at work

Client perspective

We caught a supplier disruption four weeks before it would have hit our line. That kind of lead time is the difference between a missed quarter and on-time delivery.

Bruno SantosVP Supply Chain · Apex Manufacturing

FAQ

How do you handle the data quality issues common in supply chain?
Data quality is step one. We build normalization, deduplication, and anomaly detection pipelines before any AI model sees the data. Garbage in, garbage out — we fix the garbage first.
Can you integrate with our ERP and supply chain platform?
Yes. We've integrated with SAP S/4HANA, Oracle SCM, Blue Yonder, o9 Solutions, and custom planning systems. API-first with data lineage on every flow.
How do you handle black swan events that aren't in the training data?
Scenario-based stress testing, flexible alert thresholds, and human-in-the-loop escalation for novel disruption signals. AI handles the patterns; humans handle the unprecedented.

Have Questions? Let's Talk.

Free 30 minute call with a senior engineer, not a salesperson. We have got the answers to your questions.