Pathmind
Pathmind helps simulation modelers and industrial engineers find better operational decisions by applying deep reinforcement learning to business simulations. It provides a cloud-based web application that connects to simulation tools (including AnyLogic and other simulation software) so modelers can train RL agents on Monte Carlo or agent-based models to improve scheduling, routing, warehouse control, and production decisions. The product is a B2B SaaS platform built around deep reinforcement learning algorithms and simulation integrations. Pathmind targets manufacturing, supply chain, logistics, and energy teams that use digital simulations to evaluate operational policies. The platform is used to automate complex decision-making where traditional optimization struggles.
Pathmind
Pathmind helps simulation modelers and industrial engineers find better operational decisions by applying deep reinforcement learning to business simulations. It provides a cloud-based web application that connects to simulation tools (including AnyLogic and other simulation software) so modelers can train RL agents on Monte Carlo or agent-based models to improve scheduling, routing, warehouse control, and production decisions. The product is a B2B SaaS platform built around deep reinforcement learning algorithms and simulation integrations. Pathmind targets manufacturing, supply chain, logistics, and energy teams that use digital simulations to evaluate operational policies. The platform is used to automate complex decision-making where traditional optimization struggles.
TL;DR
Core offering: Cloud SaaS applying deep reinforcement learning to simulation models for operational decision-making
Primary use cases: Manufacturing automation, warehouse control, scheduling, routing, and supply-chain optimization
Founded: 2019
Headquarters: San Francisco, California, United States
Total reported funding: USD 17,820,000
Company Overview
Problem Domain
Decision optimization for industrial operations, supply chain, logistics, and energy using simulation-driven reinforcement learning.
Founded
2019
Industry
Data and Analytics
Funding Track Record
Reported Series A closed on March 20, 2019; multiple participants reported including Presidio Ventures and Mandra Capital