40'238 Datenpunkte und eine Frage

In two months, our pilot pulled 40,238 data points from 1,834 sources. Then a client asked the one question data alone can't answer: "So what should we do about it?"

He wasn't wrong to ask.

A competitor moves into your market, files a patent, and closes an acquisition. The tools hand you a list of it happening and call that a signal, but really it's just a news feed.

That's what we built the pilot to fix. It maps an entire industry and tells clients what each move actually means for their position.

Everything it finds feeds into a weekly report, which has been running since the 22nd of April.

Of those 1,834 sources, 122 are high-level niche sources we identified and trust.

Behind them sits an ecosystem of around 80 actors we modeled: institutions, startups, scale-ups, grown companies, universities, and research labs.

That's the whole map, live and updating.

Collecting 40,238 data points is the easy part. The real work starts when you ask what any of it means.

Could it be that 3M is moving into that field? Which players in the ecosystem are affected? How does this connect to everything else?

Someone used to have to sit down and figure all of that out by hand. Now we do that computational work with our frameworks and the AI, so the client isn't left staring at raw signals.

A recent example: a startup researching the structure of pineapple leaf fiber. On its own, it's a curiosity, but in context it's a signal about where bio-based sourcing is heading, and who it touches.

So what the client gets is:

• These are the facts
• This is how it fits the market
• These are the questions you should ask yourself

And every conclusion is traceable. You can open it up and see exactly how the machine got there, all the way back to the source.

That way you spend your time building strategy, instead of validating information from the internet.