Atoptima provides an AI‑driven suite of optimization solvers that automate end‑to‑end supply chain decisions, including transport routing, 3D loading, warehouse picking, slotting, flow consolidation, and production scheduling. The platform models complex constraints such as multi‑depot routing and cross‑docking, delivering near‑optimal plans in seconds via a web interface or API integration, helping logistics providers and manufacturers reduce costs and emissions while improving operational agility.
Funding
Funding not disclosed
Founders
Product
Problem
Supply chain planning often relies on manual decision‑making and fragmented software tools, leading to high transportation costs, excess CO₂ emissions, and inefficient use of vehicles, warehouse space, and production resources. Complex constraints such as multi‑depot routing, 3D loading, cross‑docking, and production scheduling make it difficult to generate optimal, end‑to‑end plans in a timely manner.
Solution
Atoptima delivers a suite of AI‑driven optimization solvers that automate and synchronize the most complex decisions across transport routing, 3D loading, warehouse picking, slotting, flow consolidation, and production scheduling. Each solver (RouteSolver, PackSolver, PickSolver, FlowSolver, PlanSolver) models the full set of operational constraints and computes near‑optimal solutions in seconds, delivering up to 30 % cost reductions and comparable CO₂ savings. The platform can be accessed via a web‑based interface for quick data upload and visualisation, or integrated directly into existing TMS, WMS, ERP, and APS systems through native APIs, enabling seamless workflow automation. Decision‑making AI continuously re‑optimizes plans in response to real‑time events, ensuring resilience and agility throughout the supply chain.
Target Audience
Primary customers are logistics service providers, shippers, and manufacturers that operate large fleets, multi‑site warehouses, or complex production lines and need to optimise transport, loading, warehousing, and scheduling decisions at scale.
Features
- RouteSolver handles strategic, tactical, and operational transport planning with multi‑depot, cross‑docking, weekly, and multi‑modal constraints, delivering solutions 40× faster than market alternatives
- PackSolver performs exact 3D palletization and truck loading, optimizing container selection, stacking, stability, and weight distribution while visualising plans in real time
- PickSolver orchestrates order assignment, batching, picking routes, and slotting, reducing preparation time by up to 54 % and respecting traffic, zone, and turnover constraints
- FlowSolver simulates and optimises multi‑modal transport networks, identifying optimal transshipment paths, flow consolidation opportunities, and cross‑docking configurations
- PlanSolver automates production scheduling, resource allocation, lot‑sizing, and workforce planning, cutting operational costs by up to 40 % with sub‑minute computation times
- Systemic “assembled solvers” combine multiple decision layers (e.g., routing + loading + slotting) to generate globally optimal plans and capture synergy effects
- Integration options include a one‑click web‑app for CSV/JSON uploads and a full‑featured REST API for embedding into existing logistics, warehouse, or manufacturing systems
- Decision‑making AI continuously re‑optimises plans to handle disruptions, new orders, or capacity changes in real time