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Tools for Your Data Science Workbench

Accelerate Machine Learning and Cut Prep Time on Your Data Science Workbench Platform

Manual data prep and extraction is expensive. So are data scientists.

Yet, they spend at least 60% of their time cleaning and organizing data.

Why? The answer is simple. Information is tough to access because of where it’s stored or how it’s labeled in their environment.

It’s logical to think that machine-created data is also machine-readable, but it’s not. For it to be machine-readable, there would have to be one standard data structure for all organizations to follow.

If you solved the accessibility problem, you would greatly cut the time to experiment, collaborate and deploy models faster.

The end result would be much better decision-making and problem solving.

For data scientists, there is a way to easily clean and normalize all data…

Here’s How You Can Go From Research to Production Faster
and Get Better Data Science Results:

Data Cleansing Tools

Data cleansing and normalization tools shouldn’t be so difficult to use. Save significant time in cleaning data to experiment faster.

The Grooper platform wasn’t built by combining products together through APIs. Because our tools are built into one system, you can do more with original data sources.

In addition, by not jumping between tools, you can automate with high quality data cleansing tools and integration more quickly.

Data Cleansing Tools

Text Classification

Built-in text classification adds the context you need to understand the intent of a block of text.

NLP is part of Grooper’s layered AI approach, which enables a very accurate understanding of document data and text.

Text Classification

Text Extraction

As you may know, accurate text extraction is hard to achieve, even with modern OCR engines. This is because OCR needs perfect images of pages – without any defects, images, borders, stamps, bar codes, etc.

Grooper’s layered AI ensures extremely accurate text recognition along with an understanding of the information in the text.

Text Extraction

Machine Learning Tools


Data science tools like machine learning provides precision control over training.

Because of the way our data science workbench pairs layered intelligence with fine-tuned controls, machine learning project results are tied to very specific training actions, and not to black-box algorithms.

Machine Learning Tools

Augmented Analytics


Meaningful analytics and BI requires accurate data from as many sources as possible.

Augment your analytics to unlock difficult data from obscure sources like paper and electronic transactions and expand your decision-making processes to more functional and front-line roles for your employees.

Augmented Analytics

Give Valuable Business Insight and Deploy Models Faster through Grooper’s Data Science Workbench Tools

Boost your data science tasks, such as:

  • Data preparation
  • Pattern searching
  • Building machine learning models

Tools such as R, Python, or Scala transform the way you work with data, but have frustrating limits extracting large document sets. While not open source, Grooper’s open cockpit design provides transparency and fine-tune control over settings.

Grooper combines the power of open source tools with native data and document processing tasks to function as a highly efficient data science workbench.

Check out the Full Suite of Self-Service Data Tech

From data cleansing to full data integration from virtually any data source, we have a full range of tools for you!

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What is a Data Science Workbench?

A data science workbench is a self-service application that enhances data scientists usage of their libraries, technologies and analytics pipelines in a local environment to boost machine learning projects from discovery to production. With a data science workbench, data scientists can use existing skills, languages, and tools (like R and Python) already stored on their machines to run computations. They can also be used to train, deploy and manage data models for improved compliance and agility.

Data Science Workbench Testimonials

  • “Grooper will give us the access to more contract data than ever before by quickly extracting the data across thousands of lengthy contracts, allowing employees to spend time on value-adding data analysis rather than extraction.”

    Glena Brauer, Supervisor – Marketing Contracts and Compliance, Chesapeake Energy

  • “Grooper has saved OSU hundreds of thousands of dollars and the ROI was seen in less than six months after going live. This product has taken data processing, document scanning, and import automation to a whole new level. It’s now in virtually every department including our president’s office.”

    Erin Girton, Database Administrator/Content Management & Capture Administrator, Oklahoma State University

  • “Some people say information is power. I would say information gathered easily is power. If you can’t access your information easily in today’s world, it’s meaningless. Grooper gives us easy access.”


    Gary Ridley, former Oklahoma Secretary of Transportation, former Director of Oklahoma Dept of Transportation and former Director of Oklahoma Transportation Authority

  • “In acquisitions and divestitures, there’s millions of dollars at risk for us in knowing precisely what lease documents actually say versus what cover sheets say or the information being represented to us. With Grooper, you get precise information that has an impact on defects and revenue realization within the 45-day buying window. Without Grooper, you’d just be guessing.”

    Clay Chamberlain, General Counsel and Director of Legal Operations, Corterra Energy

Featured Case Studies

Thousands of companies choose BIS to enrich their environment with unique data science solutions. Here are some of their stories.

oil and gas big data case study thumbnail

Big Data Case Study

Tired of all the time & costs with manually processing documents? In this oil and gas big data case study, uncover how others are outpacing the competition.

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