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ML Engineering

The pace of model development has a great impact if there is no streamlined process or systems in place to deploy. Our Model Deployment solutions will help you build tightly coupled development, testing & production model deployment systems defining the new industry standards. Assurance of model accuracies is of utmost importance to avoid the functional product failures; our well designed and robust CI/CD pipelines will help you overcome such situations. Inspired learnings bring in the value-added composition to your table which enables you not to start from scratch again. It is in our design of development and implementation setting up the Model Development Life Cycle (MDLC) process and surprisingly Agile.

Authorization

Newly trained models can be devastating if they are not governed and authorized before they are deployed. We build highly sophisticated process for your model deployments.

Model Performance

As the time progresses the model performance would deteriorate with the change in data patterns and become obsolete. We bring in products to monitor your model performances with real time sample data sets.

Model Quality

Quality testing is much needed for ML models and as intensive as product testing. Our testing designs can keep a track and measure the quality of your models to be able to qualify for production deployments.

Autonomous

Why not have the models deploy their own once they clear the standards? Setting up solutions with autonomous systems can help you squeeze the time to market.

Product Integration

Desktop or Web or Mobile applications, it should be immaterial for your models in action. We assist in integration of models with your pre-existing products in a click, it is much needed to be able to run apps independently

Cloud

No more hassles of constraining models to be deployed and maintained on-premise. Our AWS & GCP cloud experts will manage models on cloud aiming quicker and highly performative outcomes without compromising on the product integrations.

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