For us, AI is a tool to solve practical problems -- we apply artificial intelligence and analytics to tackle challenges that arise in complex industrial settings. We call it Industrial AI.
Our expertise covers the full stack of artificial intelligence specifically focusing on solving problems arising in industrial context -- from sensing and data collection to data engineering, from computing infrastructure to machine learning models and frameworks, all the way to AI-driven services & apps and deployment.
To boost our AI development projects, we have developed proven solutions and tools for accelerated AI deployment. Our AI solutions aim to get a flying start with both initial concepts as well the productised solutions -- the solutions are customised to the specific needs and integrated as part of existing systems.
Our AI tools provide the “backbone tooling” needed in AI all projects. The tools tackle areas from generic data collection and augmentation to MLOps and to more specific purposes.
Vaisto’s Industrial AI solutions
- Predictive maintenance - Asset management, predictive maintenance and survivability
- Machine data analytics - Machine state monitoring and visualised analytics and usage predictions.
- Machine vision - Advanced machine vision solutions for solving industrial problems; e.g. measurement, situational awareness and quality assurance.
- Autonomous control - Reinforcement and supervised machine learning based control models, digital twins, use case work cycle simulations.
Vaisto’s Industrial AI tools
- Machine vision pipelines - Data annotation with smart auto-annotation and data generation.
- Synthetic data generation - Synthetic and automated data generation for custom 2D and 3D objects and environments, speeding up the dataset development and creating substantial time savings.
- MLOps - MLOps enables data science and other R&D teams to collaborate and accelerate the model development and deployment speed via monitoring, validation, automation and governance of machine learning models.
- MLOps includes
- Project template selection & customisation
- Deploy for inference
The following provides a few examples of the type of projects in which we have leveraged AI:
- Prediction models for production forecasts and optimization, as well as predictive maintenance.
- Industrial process optimization through data analytics and machine learning
- Machine vision for quality inspection, product identification, product flow monitoring and safety applications.
- Translating machine data into actionable information -- automated analytics pipeline analytics, visualizations & recommendations.
- Predictive maintenance for the materials process pipeline and related machinery will increase asset productivity while decreasing the maintenance expenses, not to mention saving time.
- Materials and resource availability in complex supply chains will provide manufacturers with new tools for optimal planning, logistics and management.
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