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Reduce friction to push models to production

We support every ML platform
Cloud | Hybrid | On-prem

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Avoid Vendor Lock-in
Reduce cost by 40%

Easily deploy machine learning models build using any ML platform in a cost effective and scalable way on any cloud or on-premise

Train and Build machine learning models at scale using hardware accelerators on any cloud or on-premise

Fast and Safe rollout of changes to production

Shortest path to gain ROI by automating ML & CI/CD Pipelines

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Support
all cloud
platform
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Automate
ML & CI/CD
pipelines
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shortest
path to
Improve ROI
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End to End ML Ops service agnostic to any cloud platform

Our approach to ML Ops is about encompassing and delivering comprehensive and flexible end to end ML services adding value to teams at any level of AI adoption maturity

One-click deployment to any cloud platform

One-click deployment to any cloud platform

Reduce cost with our automatic monitoring

Reduce cost with our automatic monitoring

Improve ROI aligning with customer growth

Improve ROI aligning with customer growth

Quick onboarding & Fasten ML Lifecycle

Quick onboarding & Fasten ML Lifecycle

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Our Partners in MLOps Service
Our Partners in MLOps Service
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Our mission is to
simplify MLOps for everyone
Today’s machine learning infrastructure is complex, with various technologies and tools used to manage the entire ML life cycle.

Our approach to MLOps is encompassing a comprehensive service that automates the deployment and monitoring of ML models wherein your Data Science teams can concentrate on building better algorithms

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We are here to truly “democratize AI”. Machine learning companies today have been focused on helping with building AI models, but in order to truly democratize AI and make it truly accessible to everyone, companies need to be ready to also ‘manage’ AI, not just build it. The AI talent gap is real, and we will help address it by reducing the dependence of expert engineers in managing AI systems.

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