Mitigating AI Risk in Banking (BFSI)

Ensure your AI program is reliable, explainable and prepared
for the inevitable audit.

1%

Enterprise companies that will
experience an audit

$ 1MM

Average cost of an
AI Audit

$ 1K

Cost to Avoid an
AI Audit
Success case for BFSI

How Data Driven ModelOps Underpins Enterprise AI Success

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Learn How Datatron Benefits Enterprise BFSI Brands

Prepare for an Audit

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Mitigate Risk & Satisfy
Compliance Requirements

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Maximize Profitability

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“Malesuada auctor habitasse ut purus varius pharetra, ut fames nibh. Amet, netus aliquet quis ac nisl pulvinar. Dui, dolor, leo, euismod luctus ac, iaculis. In lectus mattis purus justo, quis. Enim lacus molestie at mi quisque sagittis, purus. Pellentesque.”

John Smith

Group Head, Operations and Technology, HDFC Bank

Your AI Program Deserves Liberation.
Datatron is the Answer.

See what major Enterprise Brands have already discovered about
Datatron’s production-proven, Enterprise-grade AI Platform.

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Success Story: Global Bank Monitors 1,000’s of Models On Datatron

A top global bank was looking for an AI Governance platform and discovered so much more. With Datatron, executives can now easily monitor the “Health” of thousands of models, data scientists decreased the time required to identify issues with models and uncover the root cause by 65%, and each BU decreased their audit reporting time by 65%.

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Success Story: Domino’s 10x Model Deployment Velocity

Domino’s was looking for an AI Governance platform and discovered so much more. With Datatron, Domino’s accelerated model deployment 10x, and achieved 80% more risk-free model deployments, all while giving executives a global view of models and helping them to understand the KPI metrics achieved to increase ROI.

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5 Reasons Your AI/ML Models are Stuck in the Lab

AI/ML Executive need more ROI from AI/ML? Data Scientist want to get more models into production? ML DevOps Engineer/IT want an easier way to manage multiple models. Learn how enterprises with mature AI/ML programs overcome obstacles to operationalize more models with greater ease and less manpower.

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Life Cycle of Machine Learning Models

Production-grade machine-learning models require strong deployment framework in order to reduce the time it takes to iterate a model faster, deploy new features quickly, and train on incoming data faster.

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Unique Challenges Of Machine Learning Models In Production

Production-grade machine-learning models require strong deployment framework in order to reduce the time it takes to iterate a model faster, deploy new features quickly, and train on incoming data faster.

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Model Deployment

Production-grade machine-learning models require strong deployment framework in order to reduce the time it takes to iterate a model faster, deploy new features quickly, and train on incoming data faster.

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Our Latest Content

Self-Guided In-Product Tour (7 Mini-Videos)

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Experience “The Datatron” product for yourself in this self-guided series of seven, concise, mini-videos that highlight key features, like the “Model Catalog,” and “Health Dashboard,” as well as Use Cases for Data Scientists (Part III), ML Engineers/DevOps (Part IV), and AI Executives & BU/LOB leaders (Part VII). Enjoy! And, when you are ready, Book a Demo

Watch the Product Videos!