Haladir provides a unified logistics platform that integrates with existing WMS, TMS, OMS and other operational systems via a single connection. Its substrate normalizes data from these sources, and an AI‑powered engine uses solver‑grade mathematics, machine learning and forecasting to deliver real‑time optimal routing, load planning, carrier selection and inventory decisions for 3PL/4PL and high‑SKU distribution operators.
Funding
Funding not disclosed
Founders
Product
Problem
Logistics operators often rely on disparate systems—warehouse, transportation, and order management platforms—that store data in isolated silos, making it difficult to obtain a real‑time, holistic view of freight movements. This fragmentation hampers the ability to make optimal routing, inventory, and capacity decisions, leading to higher costs and missed service commitments.
Solution
Haladir offers a unified logistics platform that connects to existing WMS, TMS, OMS, and other operational systems through a single integration point. The platform’s substrate aggregates and structures data from these sources, creating a consistent data model. An AI‑powered engine then applies solver‑grade mathematics, machine‑learning models, and demand forecasting to generate optimal operational decisions at each moment. Users receive actionable recommendations—such as load planning, carrier selection, and inventory positioning—without needing to replace their current technology stack. The solution delivers continuous, data‑driven optimization while preserving existing workflows.
Target Audience
Primary customers are third‑party and fourth‑party logistics providers, as well as brand‑owned distribution and fulfillment operators that manage large, complex freight networks and require real‑time optimization.
Features
- One‑click integration layer that syncs data from WMS, TMS, OMS, and related logistics systems
- Substrate layer that normalizes and unifies heterogeneous data into a single operational model
- Engine that combines mixed‑integer programming solvers, machine‑learning forecasts, and real‑time analytics to produce optimal routing, load, and inventory decisions
- Continuous decision support that updates recommendations as new data arrives (e.g., shipment status, demand changes)
- API and dashboard interfaces for operators to view recommendations, override decisions, and monitor performance metrics
- Scalable architecture designed for global 3PL/4PL networks and high‑SKU distribution environments