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.

The End of Lookup - Rethinking Search as Infrastructure — Graphium Labs- Traditional keyword search is failing. A new, context-aware, intent-based search is emerging as essential infrastructure for better decision-making.

#SemanticSearch #DataInfrastructure #SearchArchitecture

Our latest post, www.graphiumlabs.com/blog/end-of-..., discusses how current search systems and tools are falling apart as they are required to handle an ever growing mass of data, and an increasing level of nuance and complexity.

Search You Can Trust - Graphium Labs Semantic Search Today's search tools do approximate searches or hallucinate answers. We don't. Our semantic search handles a trillion queries per month, with 100% recall & precision, finding everything that matters, ...

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

100% Recall and 100% Precision in Modern Search — Graphium Labs- Precision and recall aren’t just technical jargon—they make up the difference between trust and risk in modern search systems. And they matter more than most people think.

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.

100% Recall and 100% Precision in Modern Search — Graphium Labs- Precision and recall aren’t just technical jargon—they make up the difference between trust and risk in modern search systems. And they matter more than most people think.

New Graphium Labs blog post!
www.graphiumlabs.com/blog/precisi...

#precision #recall #relevance #search #informationretrieval #searchengineering #searchsystems #searchquality #mlmetrics

Big news: Saem Ghani (@saemg.bsky.social) is joining Graphium Labs as CEO!
He’s led SaaS + large-scale data systems for enterprise—now he’s driving our next chapter.
Come meet him & the team at Web Summit Vancouver, May 27–30. We’ll be at the booth!

Nisan Haramati on "The Limits of Scaling & The Physical Properties of Data" YouTube video by vancouver systems

Video I shot of a great talk by @nisanharamati.bsky.social on "The Limits of Scaling" at the Vancouver Systems meetup on March 10.

www.youtube.com/watch?v=D4ZL...

This was a really fun talk to give. Thanks Kir Shatrov and Cameron Morgan for organizing, and @tavis.damnsimple.com for recording!

Video: m.youtube.com/watch?v=D4ZL...
Slides: www.graphiumlabs.com/vancouver-sy...

Co-founder @nisanharamati.bsky.social gave a talk at last night's Vancouver.systems , "The Limits of Scaling and the Physical Properties of Data" going over how to predict the size limit where distributed systems stop scaling and start losing throughput.
slides: www.graphiumlabs.com/vancouver-sy...

Thank you!

Part 2: Working with Gunther's Universal Scalability Law — Hypergraph by Graphium Labs- This post will help you understand where you are on the scaling life cycle and therefore how close or far you are at any given time to a critical failure point.

We don't talk enough about Scaling to Catastrophe in distributed systems. Today's post, part 2 in the Physical Properties of Data series, explores the different scaling phases through the lens and math of the Universal Scalability Law. www.graphiumlabs.com/blog/part2-g... #databs #dataengineering

Similarity measurement is the key element in recommendation systems: which entities or objects in your dataset are similar to others, and by how much, is the engine that drives recommendation systems

Read more in our latest blog post at www.graphiumlabs.com/blog/similar...

#databs #dataengineering

The Physical Properties of Data — Hypergraph by Graphium Labs- Discover the six physical limitations of data and how hyperscaling systems must account for them in this deep dive into data’s fundamental properties.

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

The Physical Properties of Data — Hypergraph by Graphium Labs- Discover the six physical limitations of data and how hyperscaling systems must account for them in this deep dive into data’s fundamental properties.

We often think of data as an abstract virtual element, lacking mass, energy, or inertia. But data exists as physical state in physical systems, whose characteristics and constraints shape and control everything that we can and cannot do with our data.
www.graphiumlabs.com/blog/physica...

#databs