Breaking down the barriers to patenting
intellipat.ai
The Robinhood of Patents
intelliPat is an AI-powered suite of tools for patents. Its first product is Novelty Search. Simply enter some text about your idea. In about an hour we can tell you how patentable your idea is with our novelty score.
Try intelliPatWhat to Expect
IDEA
Do you have an idea for a patent? Then great! intelliPat is the right fit for you.
INPUT
Describe your patent idea to the "Novelty Search" and answer any questions that the system asks you.
PROCESS
Within 1-2 hours depending on the complexity of your idea, intelliPat performs a novelty report using AI instead of exhausted human effort.
RESULTS
Receive your results within 1-2 hours via email or on the website. You'll see a novelty score from 1-100, with 100 being the most novel idea.
Who is intelliPat for?
intelliPat is for inventors, patent lawyers, paralegals, in-house counsel, people working on intellectual property (IP), and anybody with an idea worth spreading.
More from the founders
A series of videos from the founders sharing insight, background, motivation, and context around intelliPat and the vision behind it.
Pangeon Patents
Peltier-assisted liquid-cooled computer enclosure
US7817423A computer enclosure that integrates a thermoelectric (Peltier) cooling element with a liquid cooling system to improve heat removal from components, using liquid circulation in combination with solid-state cooling to reduce operating temperatures.
System For Machine Translation
US9940321A machine translation system that processes input in one natural language, converts it into a structured representation, and translates it into a target language by combining linguistic analysis and structured memory representations to improve translation accuracy and re-assembly of output sentences.
System and Method for Artificial Intelligence
US11676058A system and method for AI that defines a framework for combining computational models to simulate higher-level cognitive functions using structured data models; designed to support automated decision-making and adaptive learning in computing systems.
System for machine translation
US10719668An updated translation pipeline that converts an input-language representation into marked-lemma dependency trees (MDTs), transforms them into a target-language representation, and outputs the translated text; MDTs can be stored/represented with embedding- or kernel-based vectorizations.