Backed by Y Combinator.
Haladir is the operational AI layer for logistics. We unify and structure data across WMS, TMS, YMS, OMS, LMS, IMS, ERP, WOS, EDI, and WCS/WES systems, and embed solver-grade optimization, ML models, RL environments for frontier AI labs, and forecasting into the decisions that power supply chains.
Haladir ingests, unifies, cleans, and structures WMS, TMS, YMS, OMS, LMS, IMS, ERP, WOS, EDI, and WCS/WES systems into a single queryable operational graph. SKUs, orders, shipments, lanes, dock doors, and labor exposed to ML and OR models as first-class objects, ready to query.
Solver-grade operations research alongside ML and forecasting, encoding the constraints that govern your operations and producing the most optimal decision within them. Vehicle routing (VRP, CVRP, VRPTW), multi-echelon inventory optimization (MEIO), mixed-integer programming (MILP), demand forecasting, ETA prediction, pick-path optimization, labor forecasting, and shift scheduling, retrained continuously on live substrate data.
Primary market: 3PLs and distributors running live freight networks (global carriers, contract logistics, cold-chain, hazmat, and brand-owned fulfillment operators).
Secondary market: frontier AI labs licensing Haladir's substrate and engine as RL environments, post-training corpora, and evaluation harnesses for models that need to reason about the physical economy.