Artificial Intelligence (AI) Cloud Platform for Enterprises

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The Journey of
Scaling Artificial Intelligence (AI)
Across an Enterprise is Hard

Unstructured,
multi-format data

Lack of
skilled resources

Time-consuming
processes

Exceptionally high
computing power

You Must Cultivate an Enterprise-wide Transformative AI Culture

Optimize day-to-day operations and ensure informed decision-making by infusing AI into core business workflows, processes, and customers’ journeys

Unlock Simple with Newgen AI Cloud

Visually manage the end-to-end data lifecycle, from preparing and deploying models to monitoring on a single unified platform. Equipped with intelligent automation capabilities, it enables users to perform key machine learning (ML) tasks within a few minutes. Furthermore, it allows citizen and expert data scientists as well as data engineers to efficiently work on AI/ML projects

With Newgen AI Cloud, You Can Do It All

From enhancing workforce productivity, fostering collaboration, speeding up the execution of data science projects to streamlining the data-to-insights journey

Prepare

Leverage an intuitive visual interface to easily prepare data at a massive scale for enterprise-wide analytics and machine learning initiatives. Ensure the reliability of results by validating the data for accuracy and consistency. Furthermore, perform various data operations, such as blend, curate, and wrangle for creating and scaling data pipelines

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Visualize

Leverage different visualization techniques, including bubble charts, scatter plots, and others to explore and easily understand data. Furthermore, prepare the data for model training by detecting and repairing data anomalies, cleansing data, and performing sanity checks using machine learning-based data validation analysis

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Train

Streamline the end-to-end data science lifecycle by leveraging an intuitive drag-and-drop interface for rapid model development, experimentation, and evaluation. Utilize in-built set of modeling algorithms to develop and deploy models on disparate datasets. Perform detailed evaluation of models through visual performance metric reports, thereby identifying, training, and optimizing for the best-fit model

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Deploy and Monitor

Identify the best-performing model from various available models set, using the built-in model recalibration mechanism, and ensure its single-click deployment. Perform model retraining on a predefined frequency, scheduled, and governed in production. Furthermore, compare and continuously monitor model performance while gaining detailed insights into its behavior

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Collaborate

Foster enterprise-wide collaboration among multiple stakeholders by seamlessly sharing assets, documents, modelling resources, etc. Easily understand each operation through comprehensive context-aware help options available at every step. Develop a long-term enterprise-wide knowledge repository for artificial intelligence models

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Automate

Automate the end-to-end recurring processes of feature engineering, machine learning model development, and model selection by using in-built capabilities. Use automated data science to achieve the best possible model performance and improve it further with automated hyperparameter tuning. Leverage the one-click option to deploy the model once it’s developed and evaluated

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Where are you in your digital transformation journey?

Problem Identification

We have compiled tools and documents to help you in your journey. Knowing that “what you see depends on where you stand,” we have something for you, as a line-of-business operations in-charge, an IT leader, or a C-level executive, for your industry-specific needs.
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Solution Exploration

At this stage, you might find that the available technology/solution is going beyond your initial expectations in terms of scope. This is also the stage of building consensus among your peers for your industry-specific needs, whether you are a line-of-business operations in-charge, an IT leader, or a C-level executive.
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Requirement Building

This stage is all about looking beyond features and functions. After all, addressing just the immediate need can translate into “short term gain but long-term loss.” Invest in a technology that solves for your today’s needs and is extensible and configurable for your unknown future needs. As a line-of-business operations in-charge, an IT leader, or a C-level executive, you don’t want to go through the same process in another 2-3 years !
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Vendor Selection

It all comes down to choosing the right partner. Their innovation history, industry focus, local presence, support services, partner ecosystem, technology strength, cost effectiveness, customer references, risk rating, and lot more needs to be evaluated. As a line-of-business operations in-charge, an IT leader, or a C-level executive, you are all evaluating them from your unique perspectives!
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Solution Optimization

That feeling of achievement and relief after a successful, on-time, in-budget project is all what you look for. Believe us, the feeling is mutual. As a line-of-business operations in-charge, an IT leader, or a C-level executive, make sure you celebrate the milestone, recognize everyone who made the project successful, and identify your additional digital needs.
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Artificial Intelligence (AI) Cloud

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The Journey of
Scaling Artificial Intelligence (AI)
Across an Enterprise is Hard

You Must Cultivate an Enterprise-wide Transformative AI Culture

Unlock Simple with Newgen AI Cloud