ONIQ provides a digital twin solution for manufacturing processes, utilizing AI-based analytics to continuously monitor and optimize production efficiency. The platform generates real-time visibility into value streams, enabling companies to identify waste and improve resource utilization while reducing operational costs.
Funding
$3.6M 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 manufacturing companies struggle with a lack of real-time visibility into their value streams, leading to inefficiencies, wasted resources, and increased operational costs. Traditional manual process mapping is labor-intensive and provides only a snapshot view, failing to capture the dynamic nature of complex production environments. This makes it difficult to identify and address the root causes of process weaknesses and improvement opportunities.
Solution
ONIQ's IQA platform provides a digital twin solution for manufacturing, offering continuous transparency into value streams and AI-based Lean improvements. The software automatically reconstructs production and logistics processes from existing IT systems, such as MES, BDE, and PPS/APS, eliminating the need for manual value stream mapping. IQA uses industrial process mining techniques and machine learning algorithms to uncover improvement potential, detect waste, and prioritize action areas. The platform integrates lean and green concepts by analyzing the energy and CO2 footprint within the value stream, enabling holistic improvements in efficiency and sustainability.
Target Audience
ONIQ targets manufacturing companies seeking to optimize their production processes, reduce costs, improve resource utilization, and enhance sustainability through data-driven insights and AI-powered analytics.
Features
- Automated value stream mapping using data from existing IT systems
- Digital twin creation for continuous capture and analysis of production and logistics processes
- AI-powered Lean analytics to detect waste and identify root causes of process weaknesses
- Real-time monitoring of manufacturing KPIs for daily shop floor management and continuous improvement
- Process carbon footprint analysis to harmonize efficiency and sustainability measures
- Automated data quality checks to identify and exclude implausible booking data
- Value stream visualizations and AI-guided analyses tailored for manufacturing
- Cloud-based platform with minimal implementation effort and no additional infrastructure required