oPROai provides an Industrial AI Platform and AI-Pilot software designed to accelerate AI deployment and maintenance in production environments. The platform delivers real-time forecasts and prescriptive control for key process variables across sectors like Oil & Gas, Chemicals, and Manufacturing. This technology augments operator decision-making to increase yield, improve energy efficiency, and enhance product quality consistency.
Funding
$3.5M 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
Many industrial processes suffer from inefficiencies due to process variability, suboptimal control, and the inability to effectively utilize existing data for real-time optimization. Traditional process control methods often struggle to adapt to dynamic conditions and complex interactions, leading to reduced yield, increased energy consumption, and inconsistent product quality.
Solution
oPRO.ai offers an industrial AI platform, AI-Pilot, that leverages deep learning optimization to provide real-time forecasts and control prescriptions for process automation. The platform analyzes existing process data to identify patterns and predict key process variables, enabling proactive adjustments to control parameters. By implementing AI-driven closed-loop control, oPRO.ai reduces process variability, improves yield and energy efficiency, and facilitates consistent operations. The AI-Pilot platform provides supervised automation control, augmenting operator decision-making and enabling Industry 4.0 initiatives.
Target Audience
oPRO.ai primarily targets manufacturing enterprises in sectors such as oil & gas, chemicals, metals & mining, and cement, seeking to improve process control, optimize resource utilization, and enhance overall operational efficiency.
Features
- Deep learning optimization for real-time forecasting of key process variables
- AI-driven prescriptions for critical control variables
- Supervised automation control for closed-loop optimization
- Reduction in process variability by half a standard deviation
- Yield and energy improvements of up to 7%
- AI Modules: Cutting-edge reusable AI components
- AI-Pilot: Yield, energy, and throughput optimization