“We thought we’d exhausted the subject.”

This phrase was overheard during an R&D committee meeting, a few weeks before a strategic project was redirected.

The context?

An innovation team had been working for several months on a new technological approach.

• Initial internal feedback was positive.

• The publications seemed promising.

• The market appeared open.

• On paper, everything indicated that they should continue.

But one question remained:

Did we truly have a complete overview of what already existed?

• Not just patents.

• Not just scientific articles.

• Not just internal memos.

  
  

  But a comprehensive analysis of everything that already existed.

This is precisely the type of situation for which we developed GraphMyTech 3.1.0.

With this new version, we’ve taken a significant step forward: the analysis is no longer limited to comparing patents, publications, and internal documents separately; it connects them!

In practical terms, this changes everything.

In this use case, the team was able to analyze, within a single map:

• patents filed by industry players;

• recent scientific articles;

• internal documents produced by R&D teams;

• common technology clusters among these sources.

This cross-referencing revealed three key signals.

First, a technology that appeared emerging in publications was already heavily protected by patents.

Second, some competitors did not appear in standard searches but became visible by combining entities, countries, classifications, and temporal dynamics.

Finally, several internal documents already referenced technical barriers identified long ago… but scattered across past notes, reports, and analyses.

In other words, the problem wasn't the lack of information; the problem was its dispersion.

With GraphMyTech 3.1.0, the team was able to:

🧠 build a common topic modeling framework for patents, articles, and internal documents;

📊 visualize dynamics by document type: country, time period, classifications, entities, and quality;

🧭 analyze clusters without artificially separating external and internal sources;

📄 integrate internal documents as a distinct document type;

🎯 leverage an improved proximity score, better able to account for multi-document matches.

The conclusion?

The decision was made to redirect the team, with better information to support decision-making.

• Less time wasted.

• Fewer resources committed to a dead end.

• An R&D roadmap better aligned with the actual state of the technology.

That's precisely our belief at GraphMyTech: The best innovation decisions don't just come from more data; they come from a better understanding of the connections between data points.

And in R&D, what you don't connect today can become a risk you only discover too late tomorrow.