Enhancing Customer Engagement with AI: A Financial Firm’s Success Story
Discover how a prominent financial institution transformed its marketing approach and improved customer engagement by integrating AI and ML
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MACHINE LEARNING OPERATIONS & ENGINEERING
End-to-end machine learning workflow processes for automated project lifecycle management with improved delivery time and reduced defects.
SIMPLIFY YOUR MACHINE LEARNING PROJECT LIFECYCLE WITH MLOPS
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MLOps is focused on operationalising the building blocks of ML lifecycle for faster experimentation, evaluation, continuous integration and deployment of the machine learning lifecycle.
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MLOps enables scalability and project life cycle management where hundreds of models can be scheduled, authored, managed, and monitored for continuous improvement.
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Machine learning models often need regulatory checks for the drifts in data, model performance and metrics, alerting at a specific threshold to enable greater transparency and faster response to such requests and ensures greater compliance.
INDUSTRY-TAILORED AUTOMATED SOLUTIONS
Automate your data and model lifecycle management
Stable Cloud Deployments
Deliver robust solutions across wide set of services to support the business with very resilience and always available services.
Cloud Agnostic Infrastructure
Drive to provided wide range of cloud platforms to develop & support multiple cloud agnostic architectures
Automated Deployment with CI / CD
Strive to make services as one click deploy, independent among developers, reduce dependencies on infrastructure
Open Source EcoSystem
Organising the architecture with various tools with strong tuning and maintenance parameters.
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