iTuring MLOps

iTuring MLOps:
Machine Learning Operations

Deploy, monitor, and govern machine learning models and enable AI at scale.

Bring DevOps like agility to Machine Learning.

Bring DevOps like agility to Machine Learning.

Research shows that only 15% of data science projects make it to production because they are so hard to deploy, and it is hard to demonstrate tangible value. Often, once AI models are deployed and face changes in real world data, they make inaccurate and unreliable predictions that negatively impact business. Complex deployment processes and legacy architecture makes retraining and redeployment of models a bigger challenge.
MLOps allows organizations to enable AI applications at scale.

MLOps for every business

With CyborgIntell, machine learning projects can be easily and automatically deployed in complex production environments in a few clicks, irrespective of where they were built. Predictive accuracy and business value is measured and improved on an ongoing basis and using CI’s Dynamic AI, models adapt to constantly changing conditions, ensuring you get the ROI you are looking for.

Deploy Monitor Govern Scale your Data Science Projects

Build models anywhere and deploy with iTuring MLOps.

With iTuring, you can deploy any ML model to your production environment in a few clicks. iTuring’s intuitive UI allows you to deploy Models written in any open-source language or library, including those built automatically using our Data Science & Machine Learning product iTuring.

Real time Decision Engine for truly digital customer journeys

iTuring scores live customer interactions in a couple of milliseconds allowing you to make real time decisions across truly digital customer journeys. Production ready rest APIs ensure that automated decision-making capability can be integrated into a company’s operations to automate decisions at rapid scale.

AI Failure Prevention with Auto Performance Monitoring

Continuously monitor and evaluate your models’ performance, track model health in real time, and KPIs like accuracy, false positives, and trends. Dynamic learning tracks drift in data, and relationship bias in algorithms to auto correct them. Manage model performance as data changes to ensure consistent predictions.

Optimize outcomes and support decision making

Transaction level ML Explanability provides you with details of key drivers that influence a prediction. AI based optimization & recommendation empowers you to manage outcomes and improve ROI. This can be used to adjust variables to either minimize (e.g., cost or risk) or maximize (e.g., profit or likelihood to buy) outcomes.

Transparency & Visibility with AI Model Governance

Maintain history of model activity in production with ability to query data, results, and code, which enables thorough audits and regulatory compliance. Approval workflows allow you to delete existing models, fall back on a challenger model or deploy a retrained model with no service interruption, while maintaining model inventory and versioning.

Value Realization – Measure the true ROI of AI Initiatives

Monitor actual business value realized through your data science projects and use cases. iTuring’ s value tracking dashboard provides you with the ability to calculate the ROI of AI and get a view of the organizations ML initiatives. Track the value of predictions across all the models deployed to understand business impact of AI.

How iTuring MLOps Works

How iTuring MLOps Works

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