Enmovil offers an AI‑native platform that unifies demand forecasting, inventory optimization, warehouse and dispatch planning, and execution monitoring into a single orchestrator for large, complex supply chains. The system continuously retrains models on real‑time signals, runs scenario simulations, and provides AI‑driven vehicle assignment, route sequencing, and load building, while its control tower delivers live visibility, risk management, and automated freight settlement.
Funding
$6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Enterprises often manage supply chain and logistics using fragmented tools that require manual forecasting, planning, and execution, leading to missed demand signals, suboptimal routing, under‑utilized assets, and costly delays. The lack of an integrated, AI‑driven orchestration layer makes it difficult to anticipate disruptions, balance inventory, and reconcile freight operations at scale.
Solution
Enmovil provides an AI‑native platform that unifies demand forecasting, inventory optimization, warehouse and dispatch planning, and execution monitoring into a single orchestrator. The system continuously retrains demand models on real‑time signals, runs thousands of scenario simulations, and balances inventory across nodes to mitigate variability. Planning modules generate AI‑driven vehicle assignments, route sequencing, and cube‑aware load building, while fleet sizing adapts to demand volatility. Execution capabilities include RFQ and bidding automation, a control tower for real‑time visibility, ETA prediction, risk management, electronic proof‑of‑delivery, and freight settlement, enabling end‑to‑end automation of the supply chain.
Target Audience
Primary customers are large enterprises in manufacturing, FMCG, automotive, chemicals, logistics, and energy sectors that operate complex, multi‑modal supply chains and require end‑to‑end automation.
Features
- Signal‑driven demand forecasting with continuous model retraining
- Scenario modelling that stress‑tests thousands of what‑if situations before disruptions occur
- Inventory optimization that balances service levels, cost, and variability across network nodes
- AI‑based warehouse planning that integrates put‑away, picking, and replenishment flows
- Real‑time dispatch planning with vehicle assignment, route sequencing, and 3D load building
- Fleet sizing tools that right‑size assets against demand volatility
- Control tower dashboard for live mile‑by‑mile monitoring and risk mitigation
- Integrated RFQ/bidding, e‑POD, ETA prediction, and freight settlement modules