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Fluid Edge Themes

NovoAI Core

Machine Learning Platform

Machine Learning Platform As a Service

Instantly provision and manage an enterprise grade Big Data distributed compute and storage platform for your Machine Learning needs. Build and deploy batch and real time Machine Learning applications on a unified platform and reduce your time to go to market for your Machine Learning applications.

Machine Learning Workbench

Self serve Machine Learning workbench

Choose from our library of prebuilt exploratory data analysis, supervised learning, unsupervised learning and anamoly detection models to build exportable and interpretable Machine Learning models. Deploy your Machine Learning models at the click of a button and have an enterprise grade Machine Learning application up and running in no time.The Machine Learning workbench also monitors the performance of models deployed in production systems and can automatically rebuild them in case performance degrades

Machine Learning Applications

Drive business outcomes using Machine Learning

Build customer segmentation, early warning systems, credit rating engines etc. using Machine Learning models built on the NovoAI Machine Learning Platform and NovoAI Machine Learning Workbench. Engage our in-house data scientists and Big Data engineers to build custom applications tailored to your specific needs.Apply Machine Learning to solve business problems end to end.

Applied Machine Learning Services

Rapidly build custom Machine Learning applications

Engage our in-house team of data scientists to build niche Machine Learning applications that suit the specific needs of your organisation. Our Data Scientists and Big Data Engineers are well versed in statistical methods, optimisation techniques,Machine Learning algorithms,Deep Learning techniques and distributed compute frameworks.

NovoAI Machine Learning Workbench

Machine Learning does not need to involve wildly expensive solutions in order to bring it to life.The NovoAI Machine Learning Workbench enables data scientists and practitioners from different fields to collaborate and build interpretable, exportable Machine Learning models.The NovoAI Machine Learning Workbench allows users to import data sets, run through Exploratory Data Analysis, build and deploy interpretable Machine Learning models using an intuitive user interface.

NovoAI Machine Learning Workflow

Import Data from various endpoints

Support wide range of data sources

Import data either from your local machine, the public web, private intranets, private cloud or public cloud into the NovoAI Machine Learning workbench. Once you have imported your data set to the NovoAI Machine Learning workbench you are ready to start the process of building Machine Learning models.The NovoAI Machine Learning Workbench has the ability to work with different file formats and missing values.At the backend, the NovoAI Machine Learning Workbench uses a Big Data distributed file system as its backend for storage.

Perform exploratory data analysis

Find patterns in your data using visual methods

Choose from a library of pre-built exploratory data analysis algorithms and find patterns in your data using visual methods.Validate hypotheses, spot outliers and get insight into the complexity of subsequent Machine Learning algorithms required to achieve your desired outcome.Exploratory data analysis a precursor to building Machine Learning models and when done right can bring about improvements in Machine Learning models by an order of magnitude

Build Machine Learning models

Build Supervised & Unsupervised Machine Learning models

Choose from our pre-built library of supervised or unsupervised Machine Learning models to meet your regression, classification or clustering requirements. Set up hyper parameters for your algorithms and train your models at a click of a button without having to write a single line of code.Our library of supervised and unsupervised models includes algorithms ranging from logistic regression to deep neural networks to non linear dimensionality reduction techniques.

Validate & Tune Machine Learning Models

Ensure the Machine Learning model has “learnt”

View accuracy measures for your classification and regression models on an intuitive dashboard to validate that the Machine Learning models have indeed “learnt” a meaningful pattern and have the ability to produce reliable classification or regression results.In addition to the standard accuracy metrics for classification and regression, the NovoAI Machine Learning Workbench also provides a visual way of inspecting model accuracy and performance.

One Click Model Deployment

Seamlessly export Machine Learning models to production

Deploy your Machine Learning models with a click to your production system.Free yourself from building prototypes, converting code from Data Science specific languages into Java code or the like to deploy to your production system. With the click of a button your Machine Learning model is deployed to production and exposed as a REST API as well.The NovoAI Machine Learning Workbench also provides the ability to combine multiple Machine Learning models into a single Machine Learning model.Model output can be viewed through either the NovoAI Machine Learning workbench or by accessing the Machine Learning model API.

Monitor Machine Learning Models


Continously monitor Machine Learning model performance

View accuracy measures of your classification and regression models on an ongoing basis and automatically rebuild the Machine Learning models in case performance degrades.This can also be used as an early warning alert mechanism to detect changes in your inflowing data sources

Prediction APIs


Integrate seamlessly with systems and applications

The NovoAI Machine Learning workbench enables users of the platform to create Machine Learning workflows either through a user interface or through an application programming interface. All actions, metrics and model scoring interfaces of the NovoAI Machine Learning Workbench are exposed as API endpoints enabling developers as well as data scientists to use the NovoAI Machine Learning Workbench in a flexible way.

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