&AI (YC S24)

&AI (YC S24)

The Definitive Platform for Patent Due Diligence

26 followers

&AI helps attorneys and inventors conduct patent due diligence for prosecution, litigation, and portfolio management. For example, we combine prior art search with detailed claim charting to robustly evaluate the validity of patents or applications.
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Launch Team / Built With
Anima Playground
AI with an Eye for Design
Promoted

What do you think? …

Caleb Harris
Maker
📌
Hey everyone! 👋 My cofounder Herbie and I are excited to launch &AI, the definitive platform for patent due diligence. We've been building &AI in this summer's YC batch as a comprehensive solution for attorneys, inventors, and more to deeply understand the patents and portfolios they work with. 📃 Patent due diligence is an essential part of the entire patent lifecycle, but notoriously difficult. By using AI to understand the inventive aspects of patents and automate the creation of work products, we enable inventors to produce robust patent applications, litigators to easily analyze patents on the basis of invalidity or infringement, and investors to understand the value of patent portfolios. ⚡ The &AI platform is built for scale. We are able to analyze thousands of patents at once, unlocking a level of due diligence that was never before possible. Our customers are already leveraging this power to find high-value licensing or acquisition targets in 1000+ patent portfolios, pitch prospective clients on case opportunities, and generate hundreds of invalidity claim charts for litigation. 🙏 We look forward to hearing your thoughts! If you’re interested, we’re actively looking to onboard more companies in the patent space. Send us a message!
Lina Lam
@harrisc congratulations on the launch!! 🥳
Elke
This sounds really intriguing, especially the way you're using AI to streamline patent due diligence! I'm curious about the specifics of how the claim charting works. How does &AI ensure the accuracy of its analysis when dealing with such large volumes of patents? Would love to learn more about the tech behind it!
Caleb Harris
@elke_qin Claim charts map claim elements to disclosures in the reference set. It's pretty straightforward to build this from an embeddings perspective but getting good results requires a lot of fine-tuning and engineering. Once you can do one very well, scaling is only a resources problem.