AI that Understands and Explains

Easy to use platform for predictive insights and simulation 

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Why Metonymize?

The Metonymize platform enables the combination of 'thinner' data with domain knowledge to produce superior explainable AI


Generative modelling approach to AI  offers ground-up support for auditability (Anti "black box")


Simulations capture human expertise 

(Intuition, Judgement)


Next generation AI compensates for limited data - generalizing insights via Transfer Learning

Solutions: How enterprises use Metonymize

Traditional Machine Learning only works with lots of data. In reality, predictive systems can combine limited data with expert knowledge using advanced AI techniques


Transfer insights for better planning​​

Consumer behavior models for concept testing at scale using simulation. Scale up experimentation while reducing marginal cost to zero.


User-driven insights from limited data 

Extend limited datasets using domain knowledge. Analyze hypothetical scenarios and conduct what-if analysis.


Consumer experience optimization

Automatically process natural language feedback in real-time. Drive operational response times down to zero to improve customer NPS.


Metonymize Platform

Full-stack architecture, easily integrated through APIs and enterprise standard web/mobile Apps

Support industry standard ETL pipelines and REST API based data input/output


5X better accuracy in language understanding.No “Cold Start” problems given pre-trained language models of semantics from different domains


Probabilistic programing libraries and tooling make it possible to seamlessly inject expert knowledge

lack of granular data to train machine learning models


Zero data generative models capture expert domain knowledge as a starting point for machine learning

Third Wave AI (3Wai) architecture supports the injection of domain knowledge to tune models with expert context

3Wai algorithms use computational capacity to “trade off” model accuracy and search time with/without more data


Scalable cloud-based High-Performance GPU enabled Compute stack for model training and efficiency

Probabilistic Computing stack delivers performance improvements with training time, even with limited data


Cloud-native API support and rapid prototyping allows for iterative design and deploy cycles for speed of integration into existing workflows


Tableau-based application deployment, for scalable, secure enterprise access


Metonymize Applications


Helps marketers experiment by replacing real-world trial and error with simulation. 

  • GAUGE drives the marginal cost of market testing to zero from tens of thousands of dollars

  • With turn-around times of minutes versus days or weeks

  • Experimentation on GAUGE is granular, auditable and iterative in real-time


Is an explainable language understanding solution for customer success managers

  • PING efficiently decodes customer behavior. Delivering insight with human-in-loop iteration

  • It delivers customizable, actionable data records from unstructured customer data.

  • Pretrained language models avoid “Cold Start” limits; 5x better accuracy with domain expertise


Turn customer feedback into actionable data for operations

  • For customer insight managers keen to drive action and NPS, Measurable and actionable bite-sized customer feedback​​


  • With API designed for easy consumption in operations workflow

  • Delivering Scalable realtime VoC access to individual department managers

How to get started with Metonymize?


Explore capabilities for your use case

Prove output with your data


Interface with workflow (APIs, Web Apps)


Enter production environment

Marie Bernard
Law, Domain Advisor

Marie is CEO of NextLaw Labs, Denton’s Venture Arm. In 2017, Dentons was ranked the #1 International Law Firm



Over 20 years of hands-on research and early-stage product development
Co-founder of EY's M&A Strategy practice, and lead Tech Partner

Kripa Rajshekhar
Founder, CEO
Alberto Moriondo
Head of Business Development

25+ years of strategy, marketing and BD across a number of industries and technologies. Leadership experience with startups and Fortune 500 companies

Led the text group on Watson Jeopardy!
Runs the Text Lab at University of North Carolina Charlotte
Visiting Professor at Duke University

Wlodek Zadrozny
NLP, Science

Two decades of experience, inventing applied machine learning solutions
Over 65 publications

Harsha Veeramachaneni
Applied Machine Learning

Senior Software Engineer, with a decade of experience in Cloud infrastructure, Clojure. Former CTO of Lumanu

Jake McCrary

Proven record of growth (P&G, Hershey’s)
Led Insights of 150+ category management professionals

Rachel Rogers
Head of CPG Growth

Advisory Board

Founder of AI Labs at both the University of Chicago and Northwestern University. Cofounder of Narrative Science

Kris Hammond
Senior Advisor

She also serves on the Board of Directors at Corning Inc., Meritage Homes, and American Eagle. Previously President of P&G’s $20B Global Beauty Sector, and enterprise eCommerce

Deb Henretta
Senior Advisor

Jim leads business development in Consumer Products & Retail, with over 30 years of experience in the industry, most of them at Procter & Gamble

Jim Prevost
Senior Advisor

Former Chief Technology Officer at The Hershey Company and Chief Information Officer at Chiquita Brands

Waheed Zaman
Senior Advisor


Backed by leading research and academic institutions, the team has a collective 100+ years of AI experience and over 100 business transformation projects at some of the most respected firms on the planet (including, IBM, P&G, EY, and Mondelez)

  • “Mined Semantic Analysis (MSA)” patent, for understanding granted by the USPTO

  • Collaborated with Harvard Business School on a study of CPG innovation and AI 

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  • Mined Semantic Analysis (MSA) presented at AAI ’15 (World’s leading AI conference)

  • Initial funding from UNC Venture incubator 

  • First Patent Filed

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