Juna AI provides AI-driven agents that automate production scheduling, process engineering, and resource management for industrial manufacturers. Its Agentic Factory OS integrates with existing IT/OT systems to deliver real-time optimization of throughput, yield, and energy consumption. The platform aims to improve utilization, reduce costs, and enhance sustainability across sectors such as chemicals, food & beverage, and pharma.
Funding
$7.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Heavy industries face challenges in optimizing complex processes, leading to inefficiencies in production throughput, increased energy consumption, higher emissions, and inconsistent output quality. Traditional process control systems often lack the adaptability to respond to real-time data and changing conditions, resulting in suboptimal performance.
Solution
Juna.ai offers an Agentic Process Control platform that autonomously manages intricate industrial processes, maximizing production throughput, boosting energy efficiency, and minimizing emissions. The platform employs industrial AI agents that analyze real-time data to optimize control strategies within existing process control systems. By continuously monitoring and adjusting machine settings, the AI agents ensure optimal operating conditions, leading to improved process stability and output quality. The platform also generates energy reports to assist companies in complying with regulations and tracking their sustainability efforts.
Target Audience
The primary target audience includes companies in heavy industries, such as manufacturing, steel, cement, and chemical processing, seeking to improve plant performance, reduce energy consumption, and enhance sustainability.
Features
- AI agents that optimize control strategies using reinforcement learning, deep learning, and numerical optimization
- Real-time data analysis and adjustments to improve throughput and quality
- Energy usage monitoring at a product level to reduce consumption and prevent peak loads
- Emission level monitoring to ensure low emission levels from production processes
- Automated generation of energy reports for regulatory compliance
- Pre-trained AI agents for specific industrial equipment, including energy, quality, production, and process agents
- Agent Builder tool to build, test, manage, and deploy tailored AI agents
- Simulation templates for fast onboarding of new equipment
- Integration with existing systems via SAP, Snowflake, and Microsoft