IoT Machine Learning
Work with data scientists who are passionate about applying their knowledge to real-world IoT problems. Our data science team consists of experts in machine learning, advanced computational science, and statistics committed to turning your data into a competitive advantage.






Our Machine Learning Capabilities
Every business needs the power to make data-driven decisions. From data cleaning and consolidation to constructing data pipelines, to building and validating predictive models, to deploying a machine learning-enabled application, Very's machine learning experts are ready to architect and develop a machine learning solution that turns your data into actionable predictions and recommendations.
Our machine learning services
• Model design, training, and validation
• Anomaly detection
• Multivariate time series forecasting
• Failure prediction
• State classification (for machines/systems)
• Digital twin
• Data quality audit
• Data warehousing
• Data / machine learning strategy
Leveraging advanced machine learning tools
AWS Sagemaker
Very's machine learning team uses AWS SageMaker to build, train, and deploy machine learning models quickly.
Python
We use the data science stack of Python packages (NumPy, Pandas, Scikit-Learn) for scientific computing in Python.
PyTorch
We use PyTorch for our deep learning-based solutions. For example, employing Long Short-Term Memory (LSTM) or Variational Auto-Encoders (VAE) for predictive maintenance and anomaly detection.
Apache Airflow
Our team leverages Airflow for workflow authoring, scheduling, and monitoring.
We have done this before, and we'll do it for you.
With a focus on mitigating risk and maximizing opportunity, we turn pivotal moments into competitive advantage.
MACHINE LEARNING
Anomaly Detection for Manufacturers
MACHINE LEARNING
Predictive Analytics to Measure Company Health
Very's data scientists came up with suggestions that were in the back of my head but I thought, 'that's probably not possible.' And they made it happen."
Anthony Connelly
FOUNDER, HOP