Get faster ROI
for your AI investments

With the award-winning Katonic MLOps platform, you can build & deploy ML models into production securely, cost-effectively & faster.

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7x

More cost-effective infrastructure

Reduction in computing costs through efficient management of data science work loads.

12x

Faster deployments

Faster and a more reliable way to deploy and improve models in production

85%

Reduction in manual labour costs

Reduction in manual labour costs resulting from higher productivity of data science teams

Awards & Recognitions

Best Practices Entrepreneurial Company of the Year Award

Best Practices Entrepreneurial Company of the Year Award

Katonic.ai awarded the ‘Best Practices Entrepreneurial Company of the Year Award’ in the APAC MLOps industry by Frost & Sullivan.​

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Everest Group’s MLOps Products PEAK Matrix® 2022

Katonic.ai featured as a major contender in the prestigious Everest Group’s MLOps Products PEAK Matrix® 2022​.

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Accredited Member of Nasscom DeepTech Club

Katonic.ai has been selected for the prestigious Nasscom DeepTech Club, a community of 300+ innovative startups from across India.

Scale & operationalise ML models and turn data into actionable real-time insights 

workflow of kaotnic mlops platform

Build with same groundbreaking open source tools that power Google, Uber, Shell and more.

The platform for operationalising machine learning

Scale your machine learning development from research to production with an end-to-end solution that gives your data science team all the tools they need in one place.​

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Accelerate experimentation

Build high-quality models and release them to production faster, with self-serve access to the latest tools and scalable compute.

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Deliver models to production

Deploy models in one click on industrial-grade, auto-scaling, Kubernetes-based infrastructure.

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Monitor and govern

Complete visibility with real-time insights and alerts on model performance with enterprise-grade security and governance.

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A Unified UI to manage all your data science in one place.

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