Skilled MLOps consultants will assess the capabilities and limitations of your current IT infrastructure, as well as review workflows for data ingestion, model training, and deployment. Next, we’ll propose an MLOps strategy tied to your business objectives, along with a phased implementation plan.

Gigbyts, an MLOps company with a knack for data management, can assist you in gathering data from various sources, cleansing and preprocessing it for ML model training, and tracking dataset versions to improve traceability and reproducibility. This results in highly accurate, bias-free machine learning solutions.

Our MLOps services include setting up cost-effective cloud-based infrastructure for training and deploying ML models at scale. Gigbyts can go cloud full swing, using platforms like AWS, Microsoft Azure, and Google Cloud, or configure on-premises or hybrid infrastructures for increased security and reliability.

In addition to consulting, we offer MLOps development services, helping clients engineer and train ML models for process automation and data analytics. When doing so, we implement tools for tracking model performance, automate hyperparameter tuning, and use distributed computing and GPU clusters for training large models.

A dedicated MLOps implementation consultant will help you ensure that your ML models meet the desired performance metrics. For this, Gigbyts will define such metrics (e.g., precision, accuracy, or recall), align them with your business goals, and use robust validation techniques, from cross-validation to holdout testing and bias detection.

Collaborate with Gigbyts's MLOps consulting team to determine the best strategy for deploying ML models into production, which can range from staged releases followed by testing and user feedback collection to running two model versions and rolling updates. We will also configure the corresponding infrastructure, including APIs and microservices.

As part of our MLOps consulting services, we help extend the principles of DevOps to the machine learning lifecycle, ensuring that models are continuously updated, tested, and deployed in a reliable and efficient manner. To that end, we use version control systems, automated test scripts, and robust performance monitoring systems.

For deployed models, we have a dedicated MLOps consulting offering. Join forces with Gigbyts to detect issues like drift, shift, and anomalies and implement logging and alerting systems to ensure those issues are promptly resolved. We’ll also help you design workflows for automatic model retraining and updating based on new data and performance metrics.