Language Intelligence applied to your use case Cortical.io delivers highly customized solutions that exactly match your requirements. Our Retina technology easily scales to any business domain, use case or language.

You can use it to locate documents, find web content, match people, identify products, monitor your competition, track customer satisfaction, discover new knowledge, and much more.

The range of business applications is truly overwhelming, from Social Media Monitoring to Enterprise Search via Information Discovery, Profile Matching, Forensic Text Analytics or Compliance Monitoring.

Just 5 steps to get a unique solution

Cortical.io’s approach minimizes the risk and investment inherent to enterprise NLP projects. The combination of breakthrough technology, use case experience and development methodology makes it possible to deliver first results very quickly and at low cost.

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Customer Intelligence

Understand your customers

Goal Extract topics from different data sources (e.g. emails, social media) and determine customers’ intents

Client Major bank

Solution

  • Extracted topics from text by filtering via meaning
  • Determined intent based on topics and sub-topics
  • Routed to correct department to take action
  • Permits statistical analysis of customer feedback

Topic detection

Goal Identify topics over time

Client Large media company

Solution

  • Converted the Twitter firehose into a stream of semantic fingerprints
  • Created one filter per user (made possible by low processing requirements)
  • Compared the stream of fingerprints to the pre-defined filter fingerprints
  • Generated a real-time content sub-stream for each user

Uncover audience needs and hidden demographics

Goal Analyze users’ queries against major search engines to identify the lexical variances across product information searches and utterances to segment audiences and more effectively answer users’ questions.

Client Healthcare — Manufacturer of Over-the-Counter Treatments

Solution

  • Integrated Retina API and 3rd party language classifier/translator to leverage latent semantic analysis in a Web-based search analysis application
  • Interrogated and analyzed >250,000 search queries
  • Reduced time required for analysis from weeks to hours
  • High-speed analysis enabled evaluation of marketing data from multiple perspectives
  • Uncovered hidden customer demographic and product uses
  • Empowered a new demographic-specific campaign and content recommendations

Search Intelligence

Document search

Goal Find documents based on meaning

Client Financial Services Company

Solution

  • Created a custom semantic space (Retina) for finance
  • Applied Retina semantic search
  • Query fingerprint is compared to fingerprints index in the Finance Retina
  • Results are ranked according to their semantic similarity with the query

Social Media Intelligence

Voice of the customers

Goal Monitor in real time what customers are saying

Client Large media company

Solution

  • Converted the Twitter firehose into a stream of semantic fingerprints
  • Created one filter per user (made possible by low processing requirements)
  • Compared the stream of fingerprints to the pre-defined filter fingerprints
  • Generated a real-time content sub-stream for each user

Data Intelligence

Clustering

Goal Improvement of data analytics models with information from free text sources

Client Automotive industry

Solution

  • Intelligent system for clustering of unstructured free text and word group extractions
  • Analyzes very specific, car-related vocabulary
  • Makes fine-grained distinctions between each car-related topic within the vocabulary
  • Detects similarities between car-related topics that are connected on the technical level
  • Works even with very short and frequently misspelled texts

Classification of messages

Goal Automatically categorize messages into classes

Client Major bank

Solution

  • Generated flexible classifier fingerprints (with keywords, bags of words or sample texts)
  • Implemented an intelligent routing system
  • Achieved 50% higher recall with the same precision as compared to production system
  • Enabled immediate evaluation of changes to the system through real-time processing