Overview

AI Features at the speed of thought

Changing business opportunities and needs are driving a more data-driven approach to growth. The increased focus on data is placing increased pressure on Data Science teams who have to deliver more AI/ML models. The quality of models is directly impacted by the quality of input data (i.e. “feature tables”) and by the breadth of feature hypotheses.

dotDataPy’s Automated feature engineering augments your ability to explore higher-order hypotheses, helps you expand your feature space, and extracts the maximum potential from complex data. 

  • Automatically explore your data to discover and build AI-features
  • Broad data-type compatibility unlocks the maximum power of your data
  • Generate feature transformation queries that are ready to deploy to production
  • Built to fit in your Python ML workflow

Augment your feature space with AI-features 

Great ML models need great features. dotData Py uses an AI algorithm to automatically hypothesize, explore, build, and validate features and AI-features augments your feature space to develop greater models.  

Unlock the maximum power from your complex data 

More data promises better performance. dotData Py explores millions of features from relational, transactional, temporal, geo-locational, and text data and discovers deeper features, automatically. Try more data with automated feature engineering and find what works and what not, faster.

Deploy feature transformers in production faster 

Production models need production features. dotData Py generates feature transformation queries with production quality and scalability. Deploy features for your ML models and deliver ML applications faster.  

Work on your Python/ML workflow seamlessly

Trial-and-error is the only way to build great features and models. With its dataframe interface, dotData Py fits in your favorite Python-based data science environment and becomes a seamless part of your iterative AI/ML development workflow. 

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dotDataPy

dotDataPy Ecosystem
AutoML 2.0 as Python Library

dotData Py provides all the power of our award-winning full-cycle data science automation from raw data through feature engineering to machine learning as a Python library. At the same time you still benefit from flexibility to customize your own AI/ML workflow on Python. With dotData Py high-skilled teams can eliminate massive amount of cumbersome manual efforts and focus the most important business problems.

Leverage Python Ecosystem

dotData Py can be easily integrated with Jupyter and other Python development environments, enabling you to leverage the power of the rich Python ecosystem. All inputs and outputs are interfaced with Pandas or Spark DataFrames. You can easily plug AI-derived features into your customized ML algorithm.

AI-Powered Feature Engineering

dotData’s breakthrough AI engine automatically discovers feature hypotheses from a massive amount of data with complex relations. By combining and correlating transactional, text, geo-location, temporal and time-series data, dotData’s AI-powered Feature engineering uncovers “unknown unknowns” that you would have never imagined and delivers deeper business insights.

White-Box AI

dotData makes your AI transparent and explainable. In addition to various model visualization, dotData automatically produces a “human-readable” explanation of each feature as well as a feature “blueprint” that visually outlines the detailed feature generation logic. In addition, dotData automatically discovered simplified forms of complex AI models with minimum accuracy sacrifice. With dotData, you can answer “why” to the AI-made decisions.

Data Science Automation Industry Solutions

Artificial Intelligence and Machine Learning can provide immense benefits to businesses across many industries. dotData’s products have been deployed in a multitude of use-cases across a broad spectrum of industries to help accelerate data science, improve performance and allow businesses to democratize AI and ML adoption.

Banking

Whether it’s mitigating fraud, modeling credit profiles, managing customer acquisition or implementing dozens of other use-cases, leverage dotData to help democratize and accelerate the process.

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Healthcare

From forecasting admissions patterns to identifying healthcare “hot spots,” dotData can help healthcare organizations to run more efficiently and provide the quality of service patients demand.

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Insurance

Managing cost is just one of the many reasons insurance companies are investing heavily in Artificial Intelligence and Machine Learning. dotData helps make the process fast, transparent and scalable.

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Fintech

Fintech companies rely on flexibility, speed of execution and technology to help drive adoption and customer satisfaction. Leverage dotData to help automate your processes and improve customer satisfaction.

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Manufacturing

Creating an efficient and speedy manufacturing process is the goal of all manufacturing companies. dotData helps you leverage the power of data science to accelerate processes and minimize waste.

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Retail

Whether it’s mapping customer acquisition patterns, modeling inventory churn or dozens of other use cases, dotData helps retailers automate the process of creating Machine Learning and Artificial Intelligence solutions.

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Marketing

Marketing has become as much science as it is art. Artificial Intelligence and Machine Learning can help create a scalable, repeatable and predictable marketing machine, and dotData can help you get there.

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