Conductiv.ai Process Control makes it incredibly easy to model complex processes and create Self-Perfecting Digital Twins for hardware equipment, chemical processes and even entire production lines, enabling effortless cost & material optimization and unlocking up to 50% reduction in product time-to-market.
With Automated Machine Learning, Federated Learning and Hybrid Modelling, the Platform enables users to rapidly model and automate complex physical systems across multiple machines and process steps. AutoML allows for autonomous algorithm selection and hyperparameter search, enabling fast and accurate AI models. Federated Learning allows for privacy-preserving data analysis across machines from multiple vendors and process steps. The Simulation Engine generates physics-based model for complex processes, empowering incorporation of cyber assets along with physical ones.
*Expose phase is open to all Experiment phase teams
Founder and CEO, responsible for overseeing the project
Cofounder and CTO, responsible for technical roadmap and strategy
Science Expert, responsible for Hybrid AI and physics simulation
AI Expert, responsible for technical development and deployment