We specialize in providing MLOps consulting services to computer vision companies to help them improve MLOps processes and practices.
Our team of experts has continuous experience in deploying, managing, and monitoring ML models in production, so we can help you optimize your MLOps processes to improve model performance, scale your ML infrastructure, and comply with regulations.
Companies often face challenges related to MLOps, such as data privacy and security, model performance and accuracy, explainability, scalability, and compliance. These challenges can make it difficult to deploy and maintain ML models in production, which can impact the overall performance and accuracy of the models, as well as the organization’s bottom line.
Our MLOps consulting services can help companies address these challenges and improve their MLOps processes and practices. We offer a wide range of services, including data privacy and security, model performance and accuracy, explainability, scalability, and compliance. Our team of experts can help you optimize your MLOps processes to improve model performance, scale your ML infrastructure, and comply with regulations.
Our success case
The well-known retail company faced computer vision-related challenges and struggled to understand the model’s decisions. Our MLOps consultants helped them to implement explainable MLOps processes and practices, resulting in improved transparency and accountability, and increased trust in the models.
Simas Jokubauskas, CEO of EasyFlow
During this stage, we will have an initial consultation with you to understand business requirements (goals and objectives), current ML operations setup, challenges, timeline, processes etc.
In this stage, we will conduct a thorough assessment of the current ML operations (ML infrastructure, including data pipelines, models, and deployment processes) and identify areas for improvement.
Based on our findings, we will provide recommendations on how to optimise ML operations, including any necessary technical upgrades or process changes.
In this stage, we will work with you to implement the recommendations and make the necessary changes to ML operations.
We will conduct tests to ensure that the changes have been implemented correctly and that the ML operations are running optimally.
We provide training to technical and non-technical teams on how to use the MLOps infrastructure and best practices for ML development and deployment.
We will decide together with you how to monitor ML operations to ensure that any issues are identified and addressed promptly.
We will provide ongoing maintenance and support to ensure that ML operations continue to run smoothly. This may include regular check-ins, updates, and any other necessary technical support.
Please note that the following process is a general outline of our MLOps consulting service. The actual steps may vary depending on the specific goals and objectives of each customer.
Improved model performance and accuracy
Increased scalability
Improved data privacy and security
Better compliance with regulations
Google Cloud ML
AWS Sagemaker
Nvidia
Azure ML
