• Rational Analytics

    Understand enterprise data, automatically.

Rational Analytics is the most accurate, cost-efficient, and defensible machine-learning-based text classification and predictive coding platform available today.

Our toolset is based on Support Vector Machine and other cutting-edge high-dimensional data classification methods, which have undergone decades of research and extensive academic peer review.

Rational Analytics enables customers to model characteristics unique to a small sample of documents and to automatically apply that model to code any number of documents. Since the quality of the output depends heavily on the input, subject-matter experts are needed to create a training set of documents for each issue by reviewing documents in a straightforward and natural manner. Typical training sets comprise only a fraction of the total document population, allowing clients to leverage the knowledge of the best reviewers across the entire dataset. RA’s experts can work directly with clients to design representative and compact training populations, specifically tailored to the document population and the substantive needs of the matter.

Rational Analytics accepts data from a variety of sources. RA clients will receive access to a custom, dedicated review environment specifically designed to allow for model training and validation during engagements. Clients will also have access to our robust, industry-leading data processing technologies should they be required.

RA is also seamlessly integrated into both Rational Governance and Rational Review. In RG, RA is used to classify enterprise documents into a policy or project for data management, thus taking the onus of organizing documents off employees. RA can also perform complex data analysis to answer any number of important business questions. In RR, RA provides an advanced predictive coding capability.


Supervised Learning

Tailor-made Support Vector Machine analysis for data classification.

Unsupervised Learning

Advanced cluster analysis for data classification.

Content Visualization

Visual representations of email communications, data distributions, and document concepts and themes.

Transparent & Comprehensible Output

Output reports display the unique characteristics of documents that informed coding/classification decisions.

Integration with RG and RR

Machine-learning applied to predictive coding, policy classification, and big data analytics.

Expert Services

Classification technology and processes customized based upon the unique characteristics of the data and the task at hand are developed, guided, and backed by our experienced data scientists.

Predictive Coding

Documents can be reviewed by Rational Analytics as an alternative to contract attorney review. A handful of knowledgeable attorneys review a small, representative sample of documents. RA’s algorithms enable the system to codify the intuition, judgment, and decision processes of these smart lawyers into a statistical model, and then automatically apply that model across a broad set of data. Each model is completely customized for the issue and the dataset at hand.

RA is not limited to coding for responsiveness and privilege – subject-matter experts can train the system for any relevant issue. Once a model is run against the entire corpus of available documents, the population is winnowed down to a manageable size for more senior lawyers to review.

The result is a more accurate, more consistent, faster document review, conducted at a fraction of the expense of manual review – thereby increasing the quality and value of lawyering. By providing transparency into the document characteristics learned by the engine as well as experts to testify to the validity of the process, our tool provides companies, their lawyers, and courts unparalleled confidence in its level of defensibility.

RA is integrated directly into Rational Review, but can also accept data from a variety of sources, including all of the primary e-discovery review platforms.

Policy Classification

Rational Analytics is tightly integrated with Rational Governance. Using only a small training set of the company’s own documents, RA can automatically classify content into any policy that exists in RG. 

For retention, an enterprise can take the onus of classifying documents off its employees.  Through RA, the system can be taught to identify which documents need kept; RG policies define where and for how long they must be retained while RG’s built in content control engine allows documents to be preserved in place or automatically moved to a records management system.    

In the same manner, RA can automatically alert RG administrators to the existence of problematic communications, or automatically move documents containing sensitive information to more secure locations.

Predictive Collection

With Rational Governance installed, all corporate content can be searched, preserved, predictively coded via RA, and then collected.  By applying Rational Analytics’ integrated machine-learning tools directly to content in place, we ensure that only truly responsive data is collected, therefore dramatically changing the economics and timeframes of e-discovery for litigation or investigation.

Big Data Analytics

The explosion of data created by and available to the enterprise presents an unprecedented opportunity for new insights into to the business environment, the mind of the customer, and the operations of the organization. Rational Analytics’ predictive modeling tools enable the analysis of potentially millions of variables to discover the key components and relationships driving complex systems and behaviors. 

RA is able to customize the algorithms at its disposal to answer any number of important business questions and help organizations gain valuable insights into how to enhance value, including market analysis, customer and competitor profiling and behavioral analysis, staffing, company culture, employee satisfaction and productivity, performance management, implicit and explicit decision-making, and a myriad of other management and operational insights. 

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