We Get IT Done

Data Engineering

AI/ML Model Design, Development, and Deployment: We first fully understand your use case. We then find precedents or existing models/ solutions that are simple and could be reused. If that’s not feasible, we create a new model/solution and deploy it for you based on our analysis. Our extensive experience in model selection and tuning and our expertise in model development ensure that the best AI model powers your product.

AI/ML Model Scaling and Production: If your data scientists have developed a model that needs scaling, our teams:
– tune the model,
– containerise the model,
– reduce latencies,
– perform orchestrations (if required),
– scale it and
– take it to production.

Your data scientists focus on developing the best model for your use case, while we ensure that it scales and we take it to production.

AI/ML Model Validation and Testing: Choosing the right model for your use case is the key driver of AI success. We validate your chosen AI model by improving input data quality and by taking a data-centric approach.We help you choose the best model for your use case and provide performance testing inputs for your models so that your model always has the best performance.

AI/ML Model Maintenance: AI models usually run in a dynamic environment with changing environments and variables. Over time, these changes cause degradation in model performance as the model has no predictive power for interpreting unfamiliar data. Our team ensures consistent performance of your model using our proprietary model maintenance framework.