All things that are needed from professional level tools that can be used by professionals and specialists in fields where making the wrong decision is simply not an option.

Ultimately, we believe that search should not create more work, it should remove barriers to action. And that’s why our Graphium Labs Semantic Search engine is built specifically to interpret intent, resolve ambiguity, and deliver precise and contextually relevant results.

We argue search needs to be reimagined as infra: not just a layer for a handy short-cut from a string of keywords to a handful of documents (that you already knew were there), but a full architectural layer in support of reasoned high stakes decision making in the age of information abundance.

I think they might be coming back. Have you seen www.graphiumlabs.com?

This post breaks down why understanding precision and recall is essential when building search and information retrieval systems for high stakes decision making:

www.graphiumlabs.com/blog/precisi...

In high-stakes environments, like medical diagnostics, legal research, and threat detection, the trade off between high recall and high precision isn’t just a theoretical optimization problem. The choice has real-world consequences.

Ideally, users want both at 100% – all (good) signal, and zero noise. But the way search works under the hood often forces a trade off: higher recall requires looser filters to bring in more results, and consequentially, more irrelevant results or noise, which bring down precision.

Precision means: “Of the results that were returned, how many were relevant (correct)?”

And recall says: “Of all the correct results, how many were returned?”

In search and information retrieval systems, precision and recall are more than just evaluation metrics—they reflect how well a system aligns with the user’s needs and expectations of relevance and completeness.

Thank you!

www.graphiumlabs.com/blog/physica...
is Part 1 of 3 of an exploration of these physical properties of data from an operator's perspective, and how they influence performance, cost, and operational limits.

#databs