What is Pathmind?
Pathmind is a SaaS platform that enables businesses to apply reinforcement learning to real-world scenarios without data science expertise. You focus on your simulation and we handle the rest.
Who is Pathmind For?
Pathmind is designed for professional simulation engineers, consultancies, and corporate teams who seek to apply reinforcement learning to their simulation projects.
Averill M. Law’s Simulation Seminars
“I have presented more than 560 simulation short courses in 20 countries and believe that reinforcement learning is the most exciting simulation-related technology to come along since agent-based simulation became popular in the early 2000s.”
Pathmind Partners
Don't have a simulation model? No problem!
Contact Pathmind to discuss opportunities to work with one of our partners who can create an RL-ready simulation for you.
Why Pathmind?
No Data Scientists Required
Experiment with state-of-the-art reinforcement learning algorithms and techniques without data science expertise. We handle it for you.
Auto-RL
Pathmind automatically handles the pain of integrating a simulation with reinforcement learning libraries, hyperparameter tuning, and setting up training infrastructure.
Deploy Real-Time Decisions
Implement your trained policies in real-world systems to make key decisions better. All Pathmind policies are available via REST API.
Recent Updates
AI Outperforms Heuristics in Call Center Optimization
Load-balancing problems like those faced in call center networks can be difficult to solve. Answering calls quickly is crucial to efficient operations, however, and long wait times can result in poor customer satisfaction. When large volumes of...
Pathmind to Present at Ray Summit 2021
Pathmind will be presenenting at this year's Ray Summit, an annual event hosted by Anyscale. Ray Summit brings together data scientists, developers, and other practitioners interested in creating scalable data and AI applications with Ray, an...
Using AI to Optimize Supply Chain Inventory Levels
Supply chain managers face a unique set of problems when it comes to optimizing inventory. Customers want their orders delivered quickly, but too much inventory in stock leads to high costs. If you factor in changing demand, backlogged orders, and...
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