KWINTELY Intelligence GmbH

Chief Executive Officer

German Aerospace Center (DLR)

Scientific Researcher

TOYOTA GAZOO Racing Europe

Calculation Engineer

AI based Patent & Science Search for Tech Companies.

Over the last decade, I helped build the Toyota F1 racing car and design crash-worthy composite aircraft structures.

Then, in 2016, I was disillusioned about working in research institutes.

So, I decided to walk away from my well-paying secure job in public service.

But I didn’t want to jump the gun.

I believed building a deep tech startup would be an incredible asset. Machine learning was the key to helping people get back in control of the gigantic amount of data being generated every day.

And I shared my thoughts. The spark was at the intersection of 4 things that changed my life. The eye-opening scheme of IKIGAI, an idea I was passionate about, the brilliance of my colleague Hardy, and my readiness to start a journey I would love to tell my kids about.

So, Hardy and I founded a deep tech startup in 2018 and matured the technology to publish a search engine for scientific literature in 2020. We found our niche with patent search in 2022 and continued to bootstrap our deep tech startup in a solopreneurial way as a team of two.


Our mission is to deliver Patents & Science intelligence with one click for instant decision making without uncertainty.

Use the Free Research Preview Version to find Patents & Science in the context of your innovation in under 5 seconds.

→ GO HERE: https://flow.kwintely.de



I share my learnings and thoughts about the process.

And if you find these valuable:

1. Follow me here on LinkedIn for more. - I’m Lennart Weiß
2. Like, share, and hit reply with your biggest takeaway!

The $634 Million Blind Spot

Picture this:

It's 2013. A meeting room in Cupertino. Apple executives sit across from Masimo's engineers, asking questions about pulse oximetry. How does the sensor work? What makes your algorithm different?

Six months later, Masimo's chief medical officer gets an offer from Apple. Double the salary. Twenty more Masimo employees follow.

By 2020, millions of Apple Watches ship with blood oxygen monitoring. 
Masimo sees their own innovations on Silicon Valley's wrists.

The jury agreed. Last week, they awarded Masimo $634 million for patent infringement on 43 million devices sold.

Apple's defense? "The patent expired in 2022 and covers historic technology from decades ago."

But here's what nobody's saying:

This wasn't an oversight. It was a choice.

Apple knew what Masimo built. They had the meetings. They hired the people who built it. They just didn't think they needed permission to use it.

The same pattern plays out across tech daily—companies racing to innovate while ignoring the IP landmines beneath their feet. Some call it aggressive growth. Others call it willful blindness.

The difference between inspiration and infringement isn't philosophical. It's documented in 270 million patents and scientific publications worldwide. Yet most companies don't check until the lawsuit arrives.

Technology intelligence isn't optional anymore.

Not when a single overlooked patent costs you $634 million. Not when your competitor's R&D roadmap is public record if you know where to look. Not when context-aware search can map your entire competitive landscape in under 90 seconds instead of three months of manual research.

The truth? Apple will appeal. They have the resources. Most companies don't.

The lesson isn't about Apple.

It's about you. Every invention disclosure crossing your desk. Every product feature your team wants to launch. Every "innovative" solution that feels too good to be true.

Before you hire that expert, before you launch that feature, before you patent that invention ... you must know what already exists. Not with keywords and hope. With context and certainty.

Because freedom to operate isn't just a legal checkbox. It's the difference between building on others' work and stealing it.

Move fast, yes.

But look first.

Do you?

Dr. Lennart Weiß

Technology Intelligence with Context Search in Patents, Science, and Clinical Trials for Executives in IP and Innovation | AI Expert | Speaker

Patent data is easy to process. 

Until you actually try to process it. 😅 

Everyone assumes you just pull patent data and start analyzing. 

Sounds simple, right?


Then you hit your first 10,000 duplicate entries, watch your metadata fields collapse, and realize "easy" was someone else's problem to solve.

On top of that you have to handle patent data like the one shown in the image.

WTF!


Most patent intelligence tools gloss right over this. 

They show you pretty dashboards and call it done. 

They don't show you the unglamorous work of making data actually reliable.


At Kwintely, we're obsessed with the part nobody talks about: data quality. 

Because bad data doesn't get prettier ... it just gets worse. 

At scale (but that is a different topic).


If you're building on patent data, the question isn't whether it's easy to process. 

It's whether you trust what you're building on.

In case you want to learn more about context search and quality of patent data go here: https://lnkd.in/euwFydjB

“We have a patent, so we’re safe.”

THE most dangerous misconception a LifeScience CTO can possibly have!

Here is why:

If that sentence were true, a lot of patent lawyers would suddenly have much less to do. 

A patent is a beautifully framed right to exclude ... not a golden ticket to manufacture whatever sits in your claim 1.
​
You can proudly own a patent on a clever improvement and still infringe a broader, older patent the moment you go to market. 

The law does not care that “but ours is more innovative” sounds great in a pitch deck.
​
That is why serious teams treat Freedom to Operate as a continuous discipline, not a box to tick before launch. 

Kwintely helps by turning patent and science data into a context map: who owns what, where, and how it touches your technology, backed by unique quality data.
​
If your roadmap still equates “patented” with “safe,” it might be time to upgrade both your IP mindset and your data quality ... starting with your technology intelligence platform.

What's your current approach?


PS: 
check out flow. kwintely. de

The blackboard sat empty when Richard Feynman died.

On it, scratched in chalk: 

"What I cannot create, I do not understand."

It wasn't a riddle. It was a confession. A principle so fundamental that it shaped everything he did ... from taking apart radios as a boy to writing equations on napkins in diners. 

Feynman believed understanding wasn't something you passively received. It was something you actively built.

You know this already, in some part of you.

Think about the last time you tried to truly understand something. Not memorize it. Not read about it. Understand it. You probably had to recreate it. Rebuild it. Put your hands on it. The moment you could construct it from first principles ... that's when it clicked.

Here's where this gets interesting for you.

You work in technology intelligence. You're swimming in reports, patent filings, competitive data. You could spend your entire career absorbing that information. And you'd still be behind the companies that create their own intelligence systems. That reconstruct their market from scratch. That build their own mental models of how their industry actually moves.

Those companies don't just know their segment. They understand it. And because they understand it, they move through it faster. They see what's invisible to everyone else. They build faster. They execute with a speed that seems almost unfair to outsiders.

Speed comes from creation. Creation comes from understanding. 

Understanding comes from building it yourself.

Dominate your industry segment through information superiority. 

Build your intelligence framework from first principles. 

Create the map. 

Because when you create it, you own it. 

And when you own it, you move like no one else can.

Do you agree?

“Don’t worry, we only use your search intent to improve the experience.”

Translation: 

we also improve a lot of other people’s experience with your data.

Modern search has a funny habit of treating your questions as community property ... great for ad targeting, terrible for sensitive innovation work.

​
In patent and science search, that’s absurd.

You’re mapping future products, not shopping for sneakers.

Your intent should not be the next data point in someone else’s dashboard

That’s why Kwintely runs on its own infrastructure, with its own data quality pipeline, and keeps your search behavior out of third-party ecosystems.

​
If you’re serious about technology intelligence, stop donating your search intent for free.

Ask whether your current tools protect both data quality and intent ... or come talk to Kwintely about a setup that does.


PS:

Learn more in confidential search here:
 https://lnkd.in/eue6ZPj8

​

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