Maneva Raises $27 Million to Tackle Inefficiencies Across the $46T+ Manufacturing Industry

Maneva, the physical AI solution provider specializing in video-to-action intelligence for manufacturing, led by Rae Jeong and Kelvin Chan, has raised $27 million in Series A funding led by U.S. Venture Partners, with participation from returning backers Bling Capital and Freestyle Capital, alongside a group of leading angel investors. 

Building The Operating Layer For Modern Factories.

The new funding brings total capital raised by Maneva to $38.4 million, with support from existing investors including Gokul Rajaram. The capital will be used to advance AI vision technology, expand internationally, and accelerate deployment of factory orchestration tools and AI knowledge agents.

Maneva is developing a data and control layer for manufacturing that uses proprietary physical AI and vision-language models to transform existing factory camera networks into real-time operational intelligence systems. Rather than requiring costly infrastructure replacements, the platform analyzes factory operations through edge-based computer vision, identifying problems, diagnosing root causes, and triggering corrective actions as they occur.

The company is targeting a major industrial challenge: many manufacturing facilities operate at roughly 60% Overall Equipment Effectiveness (OEE) due to fragmented systems, limited visibility, and slow operational decision-making. These inefficiencies contribute to an estimated $1.4 trillion in annual losses from unplanned downtime across the manufacturing sector.

Addressing Growing Manufacturing Complexity.

Manufacturers are facing increasing operational complexity, with supply chain disruptions, production challenges, and rising efficiency pressures becoming widespread across the industry. At the same time, industrial operations remain one of the world's largest consumers of energy, making productivity improvements a critical priority.

Maneva is tackling this challenge with an AI-powered platform that acts as a real-time operational brain for factories. Using existing infrastructure, the system helps manufacturers improve uptime, productivity, quality, and safety by continuously monitoring operations, identifying inefficiencies, and enabling faster decision-making, without requiring new hardware deployments or cloud-based systems.

Advancing Factory-Floor Operations With AI.

Maneva uses its proprietary VITA and ALIS models, deployed on NVIDIA edge devices, to transform existing factory cameras, sensors, and equipment signals into an intelligent operational system.

The platform continuously monitors factory operations, identifies safety risks, inefficiencies, and bottlenecks, determines likely root causes, and can trigger automated actions across equipment, workflows, and teams.

Key benefits include:

• Reduced downtime: Early detection and resolution of operational issues can significantly improve production uptime and increase output.

• Higher labor productivity: AI-assisted monitoring and workflow optimization help workers focus on higher-value tasks, boosting overall productivity.

• Improved quality control: Real-time defect detection enables faster intervention, with AI models achieving accuracy levels of up to 99.9%.

• Enhanced workplace safety: Continuous monitoring of compliance and operational risks helps improve health and safety performance across facilities.

  
  

By combining computer vision, operational data, and automation, Maneva aims to help manufacturers improve efficiency without requiring major infrastructure upgrades.

Growing Adoption Across Manufacturing Industries.

Maneva is already working with manufacturers across sectors including confectionery, wood products, glass, steel, meat processing, food and beverage, pharmaceuticals, cosmetics, and distribution.

Rae Jeong said manufacturing remains one of the world's most important industries, yet continues to suffer from significant inefficiencies. He believes manufacturers have an opportunity to reduce waste, improve productivity, and optimize energy usage by gaining greater visibility and control over factory operations through AI.

Matt Garratt highlighted Maneva's combination of advanced computer vision, reinforcement learning, and robotics expertise. He noted that the platform addresses longstanding challenges associated with legacy manufacturing systems by eliminating the need for proprietary hardware, extensive customization, and service-heavy deployments, while providing operators with visibility across entire manufacturing networks.

A CIO at a Fortune 500 industrial manufacturer also praised the team's execution capabilities, citing the company's ability to deliver measurable operational impact and describing Maneva as an emerging leader in industrial vision AI.