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Optimind

Category: AI in Supply Chain / Logistics

A cloud-based AI route optimization platform specializing in 'last-mile' delivery that automates complex vehicle routing and scheduling to improve logistics efficiency. Optimind was founded in 2015. The company is led by Ken Matsushita. Based in Nagoya, Japan. Team size: 70. Total funding raised: $22.0M. Latest round: Strategic investment (Undisclosed, Mar 2025). Key investors include ["Toyota Motor Corporation","SPARX Group (Mirai Creation Fund)","KDDI Open Innovation Fund","Mitsubishi Corporation"].

Founded
2015
Headquarters
Nagoya, Japan
Team size
70
Total funding
$22.0M

Value proposition

Solves the '2024 Logistics Problem' by reducing driving distance and vehicle requirements through AI-driven route optimization that improves over time by learning from real-world driver behavior.

Products and solutions

["Loogia (Flagship AI Route Optimization Cloud)","Loogia Connect (Integration API for WMS/ERP systems)","Loogia Driver App (Real-time dynamic management and navigation)","ScaLe (AI system for optimized staff assignment and visit scheduling)","Loogia Consulting (Simulation-based logistics strategy and BPaaS)"]

Unique value

Utilizes a 'Data Circulation' model where the AI continuously learns from billions of real-world GPS and dashcam data points to provide hyper-accurate travel time estimates.

Target customer

Logistics providers, food and pharmaceutical wholesalers, home healthcare services, and retail delivery operators managing last-mile fleets.

Industries served

["Last-mile Logistics & Courier Services","Food and Beverage Wholesale (e.g., Bourbon Corp)","Pharmaceutical Distribution","Home Medical Care & Nursing","Automotive & Manufacturing"]

Technology advantage

Employs advanced meta-heuristic and combinatorial optimization algorithms combined with machine learning to complete data for unknown routes and accommodate complex real-world delivery constraints.

How they differentiate

Utilizes a 'Data Circulation' model where the AI learns from billions of real-world GPS and dashcam data points to estimate hyper-accurate travel times and parking constraints that standard map data cannot capture.

Main competitors

["Hacobu (MOVO Fleet)","Zenrin (Route Optimizer)","Locus","Fujitsu (Logifit)"]

Key partnerships

["Toyota Motor Corporation (Mobility service collaboration)","Mitsubishi Corporation (Logistics innovation partner)","Seino Transportation (Joint API verification 2024-2025)","KDDI (Strategic investment and growth support)","Japan Post (POST LOGITECH INNOVATION PROGRAM winner)"]

Notable customers

["Japan Post","Toyota Motor Corporation","Seino Transportation","Bourbon Corporation","Kakuyasu"]

Major milestones

["Winner of the Japan Post POST LOGITECH INNOVATION PROGRAM (2018)","Launched flagship AI routing service 'Loogia' in Sep 2018","CEO Ken Matsushita recognized in Forbes 30 Under 30 Asia (2020)","Series B funding of 2 billion JPY secured in Dec 2022","Strategic investment from NOBUNAGA Capital Village for regional expansion in Mar 2025"]

Growth metrics

Cumulative funding reached over 3.1 billion JPY (~$21M+ USD) prior to its 2025 round; designated as a 'J-Startup' by Japan's Ministry of Economy, Trade and Industry (METI).

Market positioning

Leading specialized AI route optimization provider in the Japanese last-mile logistics market.

Geographic focus

Primarily Japan, with strategic expansion focus on the Asia-Pacific region.

Patents and IP

Holds proprietary patents related to its core route optimization algorithms and AI-based speed estimation models for logistics.

About Ken Matsushita

Ken Matsushita founded Optimind in 2015 while a student at Nagoya University. He is an expert in combinatorial optimization algorithms and meta-heuristics. He completed his Master's and reached the doctoral candidate stage (unit-acquired withdrawal) at the Nagoya University Graduate School of Informatics. He currently serves as a Specially Appointed Faculty member at Nagoya University and was recognized in Forbes 30 Under 30 Asia in 2020.

Official website: