Unlock meaning like never before

Forge closer relationships with your users through deeper understanding fueled by Natural Language Processing and Machine Learning. Codeq is focused on empowering your firm to smartly leverage these technologies to enable your digital transformation.

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What We Offer


Accelerate your digital transformation process with NLP (text processing) guidance and solutions from Codeq.


As a natural language processing consultancy and technology company, we offer end-to-end strategy, services, and tech.


We meet you where you are and help take you to where you want to go by extracting business intelligence from human language text and delivering the most accurate reporting and analysis.

Interested in learning more?

We love talking with new potential partners in the B2B, defense, or consumer spaces.

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Let our team of computational linguists, engineers, and consultants help you use NLP to derive meaning from unstructured data.

NLP Consulting

  • Planning  Analysis and development of requirements. Assess project feasibility, cost, and timetables.

  • Architecture  Direction in developing system architectures that integrate seamlessly with existing infrastructure.

  • Project Remediation  Help in quickly correcting troubled projects and providing recommendations for increased performance.

Solutions Deployment

  • Development and launch of new or innovative Codeq natural language processing solutions.

  • Additional capabilities include data acquisition, raw language and statistical language processing, and text mining and extraction.

Codeq Technology Implementation

  • Research, design, and implementation of Codeq’s proprietary natural language processing technology.

  • Scalable framework that is easy-to-use and cost-effective.


In 2014, a small group of scientists, engineers, and designers set out to change the way we look at digital content by harnessing powerful computing algorithms.


  • Boutique-like domain customization
  • Flexible deployment options
  • Simple API design and integration
  • Developed in Python
  • Powered by well-known Deep Learning toolkits
  • Rule-based + ML/DL modules

High Level Modules:

  • Language Identifier

  • Named Entity Recognition

  • Named Entity Linking

  • Named Entity Salience
  • Speech Act Classifier
  • Question Classifier
  • Sentiment Classifier

  • Emotion Classifier
  • Sarcasm Classifier
  • Coreference Resolution

  • Date Resolution

  • Task Extraction

  • Sentence Compression
  • Summarization

Low Level Modules:

  • Tokenization

  • Sentence Splitting

  • Stopword Removal

  • Stemming
  • True Casing

  • Detrue Casing

  • POS Tagging

  • Lemmatization

  • Dependency Parser

  • Chunker

  • Semantic Role Labeling

Past Work Featuring our Technology


Paulo Malvar Fernández


Paulo is Codeq’s Chief Computational Scientist. With more than a decade of experience in designing and building complex NLP solutions, he has lead Codeq’s team of computational linguists in designing and building NLP products for such use cases as NLP-powered email clients; websites performing opinion mining, topic detection, and statement matching on customer reviews for major app store platforms; and development and training work in statistical and rule-based machine translation systems for various language pairs.

Paulo earned an undergraduate degree from the Universidade de Santiago de Compostela and graduate degrees in applied linguistics and computational linguistics from Pompeu Fabra University and San Diego State,respectively.

Rodrigo Alarcón Martínez


Rodrigo is a subject matter expert and consultant in computational linguistics, specializing in natural language processing, text mining, information extraction, knowledge discovery, semantic web, and terminology.

He has more than a decade of professional experience in natural language processing in academia, large-scale enterprises and tech start-ups in the US, Germany, Spain and Mexico.

Rodrigo earned a Ph.D in Language Sciences, with specialization in computational linguistics from University Pompeu Fabra University. His work has won the International Award for Outstanding Achievement in Applied Research and Development, from the European Association for Terminology.

David Schueler


David is a subject matter expert and consultant in computational linguistics. He helps develop NLP tools, such as part-of-speech taggers, parsers, and chunkers, and helps partners leverage those in solutions that help with tasks such as summarization and compression of text.

In addition to this experience, David also has extensive teaching experience, having served as a visiting assistant professor in linguistics at the University of Illinois at Urbana-Champaign and the University of Minnesota, Twin Cities.

David holds a Ph.D in linguistics from the University of California, Los Angeles and an undergraduate degree in linguistics from the University of Pennsylvania.

Brian Fernandes


Brian leads server/database development for Codeq, designing, implementing and deploying distributed scalable solutions in support of Codeq-architected solutions. Brian’s diverse engineering experience in a wide range of problem spaces began with key software engineering roles in multiple early internet startups. While working at Sony Computer Entertainment America (SCEA), Brian helped develop and launch Playstation’s first multiplayer gaming platform…

…and supported the development of immensely successful game titles, including the SOCOM franchise, Ratchet and Clank, and NFL GameDay. His work here led to his co-invention of multiple SCEA patents in distributed game server design.

Brian holds a BS in Mechanical Engineering from the University of California – San Diego.

Russ Smith


Smith is a versatile professional with business acumen and expertise in product development. He enjoys working with empowered engineers and is passionate about product. Prior to joining Codeq, he managed a team of product managers working on Yahoo Mail for iOS, Android, Windows 8 and mobile web.

Dane Baker


Dane Baker started Codeq in 2014 to meet a growing need he saw as an app developer; Could thousands of app store reviews be distilled into providing useful insights? The team’s first product, CrowdChunk, was a database powered by Natural Language Processing and Machine Learning that aggregated app reviews and broke them down into actionable highlights.


Visit our blog

Emails Analyzed

Parsed and summarized by the Codeq API, allowing users to save time by reading less email.


Tasks Extracted

Calls to action generated from unstructured text.


News Summaries Generated

Time saved by producing more meaningful text, generated in real time.