AI Solutions for Logistics & Supply Chain Operations

Our routing engines utilize hybrid metaheuristics and integer programming to solve VRP issues under strict constraints.

We integrate custom solvers built on Google OR-Tools and Tabu Search algorithms with GPU acceleration. This setup allows the system to process vehicle stops, driver Hours of Service (HOS) restrictions, vehicle weight parameters, and narrow customer delivery windows simultaneously in less than 60 seconds, avoiding the limitations of traditional sequential scheduling tools.

We deploy layout-aware Transformer models trained specifically to read skewed, low-contrast, and handwritten logistics documents.

Unlike standard OCR systems that output plain text blocks, our system analyzes spatial coordinates alongside text embeddings. This approach preserves table alignment, connecting commercial invoice line items, container numbers, and HTS codes with 99.8% extraction accuracy. Mismatches are flagged before submission to customs ports.

Yes, our systems integrate with SAP, Oracle, and other legacy ERPs using standard APIs and event streaming protocols.

We construct bidirectional middleware interfaces using SAP IDoc, Oracle SuiteTalk, or Kafka event streams. The models pull inventory targets and order logs from the ERP, compute routing parameters, and push the results back to update shipment records without causing database transaction locks.

All logistics data is secured using enterprise-grade encryption and isolated private cloud environments.

We run model inference inside your dedicated VPC (AWS, Azure, GCP) or on-premise hardware. Data is encrypted using AES-256-GCM at rest and TLS 1.3 in transit. Our de-identification gateway filters out sensitive cargo and pricing identifiers upstream of any model call, maintaining strict compliance schedules.

Our models combine live AIS GPS tracking streams with historical port delays to estimate maritime ETAs.

We train transformer sequence models to analyze historic vessel paths, current weather conditions, and port queues. The model continually updates its predictions, outputting milestone ETAs with a P95 confidence score that outperforms standard maritime tracking services.

Standard navigation tools calculate routes for single vehicles, whereas our engines optimize multi-vehicle fleets simultaneously.

Our systems run combinatorial optimization algorithms that allocate stops across a fleet, reducing total mileage and cost. We balance load distributions, ensure drivers return home within HOS limits, and match specialized cargo with refrigerated trailers, which standard consumer mapping interfaces cannot resolve.

Yes, our cold-chain software meets FDA Title 21 CFR Part 11 and other global standards.

We build telemetry ingestion pipelines that encrypt temperature, humidity, and vibration logs directly from BLE sensors. This data is recorded in audit ledgers to generate tamper-proof reports, ensuring compliance during transit.

Deployments primarily save costs by reducing empty miles, automating customs paperwork, and optimizing inventory volumes.

Fleets typically see a 12-22% drop in empty miles through backhaul matching, a 75% reduction in document processing hours via Document AI, and lower storage costs through SKU demand forecasting. These improvements combine to deliver a rapid return on investment.

Autonomous agents parse alerts, research options, draft updates, and execute recovery steps within defined boundaries.

When a shipment delay occurs, the agent reads the status, searches for alternative carriers on load boards, checks contract rates, and drafts a new itinerary. If the solution fits your budget limits, the agent updates the TMS record automatically.

A custom routing engine takes 12 to 16 weeks to build, test, and integrate into production systems.

We start with a 4-week feasibility pilot to analyze data pipelines. The remaining time is spent building optimization algorithms, integrating with WMS/TMS platforms, and executing validation tests before launch.

Our forecasting models analyze external market indices and shipping bottlenecks rather than relying on historical data alone.

We feed models with import data, carrier search queries, and regional weather alerts. This allows the system to adjust safety stock targets and routing options before disruptions affect your supply chain.

All logistics AI systems act as assistive tools that include human oversight checkpoints.

Our systems are designed under the guidance of Umar Abbas, Principal AI Architect. The software automates administrative tasks and calculates routes, but requires human operators to approve spot tenders, final customs filings, and dispatch updates.