Supply-Chain & Logistics AI
Move goods smarter — routing, ETA prediction, warehouse vision, and shipping-document automation, integrated with the systems you run.
The problem
Logistics runs on thin margins and manual coordination. Routes are suboptimal, ETAs are guesses, exceptions eat coordinators’ days, and every shipment drags a stack of documents.
What it includes
The capabilities we build into this solution — engineered for production, not a demo.
Route optimization
Optimize routing against cost, time, and constraints in the real world.
ETA prediction
Accurate, updating ETAs from your operational and external data.
Shipping-document automation
Read and generate BoLs, customs, and manifests automatically.
Warehouse vision
Computer vision for counting, inspection, and put-away.
Exception handling
Agents that triage and resolve the exceptions that clog the day.
Systems integration
Connects to your TMS/WMS/ERP with monitoring.
How we'd build it
The same method behind everything we ship: de-risked, measured, and in production in one quarter.
Feasibility
We validate the use case on your real data, define the accuracy bar and ROI, and give you an honest go/no-go — usually in weeks.
Build & evaluate
We engineer the system and score it against a labelled set until it clears the bar — quality is a measured number, not a promise.
Deploy
We ship to production, integrated with your systems and behind the right human-approval gates, with monitoring from day one.
Operate & improve
We watch it in production, handle drift, and expand scope as trust builds — feasibility in 6 weeks, production in ~90 days.
What you get
- Optimized routing and more reliable ETAs
- Automated shipping-document handling
- Faster exception resolution
- Integration with your TMS/WMS and an audit trail
Production AI we've shipped
We'd build your solution with the same discipline behind these real, in-production engagements — described by sector under NDA.
A production document classifier — 5,000+ documents/month, built to a ≥95% accuracy target and live in 8 weeks.
Read the case studyBank-statement automation across 21 banks with a measured 0.24% transaction-direction error rate.
Read the case studyAI-at-POS recommendations running against live in-store transactions across every location.
Read the case studyWant to scope Supply-Chain & Logistics AI?
Tell us the use case. We'll come back with a feasibility view and an honest go/no-go — a working prototype in about six weeks.
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Location
Barcelona, Spain • Lisbon, Portugal • Sheridan, WY, USA (incorporation)
Why Choose CONE RED?
- AI R&D lab & venture builder — production systems, not slideware
- Feasibility in 6 weeks, production in ~90 days
- Accuracy measured and evaluated — never invented or guaranteed
- Real engagements across financial services, healthcare & retail
- End-to-end support from strategy to deployment
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