Basetwo AI provides a low-code platform for manufacturing process optimization across industries like pharmaceuticals and specialty chemicals. The platform enables users to build explainable digital twins for faster process development and scale-up. This results in reduced experimentation time, lower manufacturing costs, and improved quality control through real-time soft sensing.
Funding
$17.4M 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.
+4Founders
Product
Problem
Manufacturing process engineers often struggle to improve productivity, quality, and efficiency due to a lack of scalable tools for operationalizing machine learning. Process knowledge remains siloed in spreadsheets and individual engineers' expertise, hindering widespread optimization efforts. Existing machine learning platforms often fail to address specific engineering challenges and lack the scalability required for full operational deployment.
Solution
Basetwo offers an AI co-pilot designed to provide real-time recommendations for optimizing manufacturing processes. The platform enables engineers to integrate data from multiple sources, build and validate machine learning models, and deploy these models to enhance standard operating procedures. Through a low-code, drag-and-drop interface, Basetwo simplifies the creation of digital twins, allowing for process simulation and the identification of optimal plant controls. The platform facilitates data-driven decision-making, helping to reduce energy and material consumption, streamline cycle times, and improve overall quality control in complex engineering environments.
Target Audience
Basetwo targets process engineers, manufacturing directors, and process modelers in industries such as pharmaceuticals, specialty chemicals, consumer packaged goods, building materials, and gas processing.
Features
- Low-code, drag-and-drop interface for building and deploying AI models
- Integration with existing databases like OSI PI for seamless data ingestion
- Generative AI assistant for data transformation and cleaning
- Process simulation using historical data to create digital twins
- Real-time recommendations generated by reinforcement learning for process improvements
- Role-based access control