Labos, Shacham Street 32, Petah Tikva (2026)

22/10/2026

Generating genomic data in your clinical lab? Let's be honest - that's the easy part. The major challenge is (and always has been) making that data accessible, interoperable, secure, and clinically useful.

Be honest in the comments when you tell us how your lab conquered Terabytes of data per patient, complex integrations, strict compliance, and sequencing volumes that keep climbing. Really, be honest - because we've talked to so many labs that realized that without the right infrastructure, more data is basically more complexity, not better insights.

These labs were desperate for a solution - and you know what the first thing we did was?

No, we didn't try to sell them our groundbreaking LIS platform. No, we actually sent them to go over our Decoding Laboratory Information Genomic Big Data breakdown -

https://eu1.hubs.ly/H0z9s9x0

We think ckabs deserve better - and we're always on the lookout for new ideas. Tell us how your lab figured out the genomic data challenge?

19/10/2026

Single Sign-On (or SSO) is the simplest way for lab staff to authenticate once and then access every connected application without logging in again. It’s the literal real-world version of the coveted “one click of a button” scenario: One identity, many systems, a single front door for the whole shift.

However... So many labs still haven't adopted it. And we don't get it. The hidden costs of all those logins go far beyond time saved. We broke it all down right here: https://eu1.hubs.ly/H0z5-b20

Is your lab using SSO? If not - why?

16/10/2026

Most legacy LIS vendors treat “interoperability” like a marketing buzzword. But then, your lab buys it, and reality hits: You're still stuck with batch delays, clunky custom code, and zero real connectivity. And if you need an interface to a new outreach clinic or specialty analyzer?

No problem! That’ll be six months of waiting and a six-figure change order.

So, hoping you’ll save your precious time with such vendors, here are the 5 dirty secrets why most LIS vendors fail at true interoperability:

1. They’re slapping APIs onto 90s monoliths

2. They treat "point-to-point" as though it equals integration

3. They nickel-and-dime every connection

4. They force your lab into their legacy, rigid, limited box

5. Engineers built it, but lab pros didn't guide it

And what is true interoperability across fragmented networks, you might ask?
There you go: https://eu1.hubs.ly/H0ywPTF0

What is the most frustrating experience your LIS vendor put you through? Share your stories - maybe we can find the 6th secret 🙂

13/10/2026

Data centers are dominating headlines right now because of AI hype, massive energy draw, and physical footprint debates. In the good case scenarios, public opinion will treat them as a speculative tech dilemma. In the worst cases, we’ll hear claims such as “concrete fortress pulling up to 100 kW per rack and drinking millions of gallons of water a day just to keep from overheating“...

However, we’d like to offer a middle ground: for clinical laboratories, cloud data centers they are a life-or-death operational reality.

The server room down the hall from your instrument bay? That’s actually a ticking time bomb. A failed cooling unit, a fried power supply, or someone accidentally kicking a network cable…? Any of those rea;-life examples will paralyze testing workflows for days.

And that’s just the tip of the iceberg - but also - we've got some best practices for you - all neatly summarized in our latest breakdown:

https://eu1.hubs.ly/H0yS58-0

Tell us - is your lab working with a cloud data center? What do you think are the pros and cons?

07/10/2026

Just in case you missed it (and we’re confident that you didn't) - the past few weeks have been a whirlwind of Anthropic lab-related news: numerous updates about Claude integrating with pathology tools for tissue analysis and research.

However, it’s not fully autonomous - and not for lack of trying. Here’s the catch:

Anthropic operates an in-house wet biology lab, where Claude directs robotic equipment and runs physical tasks. For now, this “autonomous lab” focuses on fundamental biological research and drug discovery, not clinical or pathology diagnostics. But it’s only a matter of time, right? Well…

What no one really says out loud is that, yeah, you can definitely build the smartest model on the planet, but clinical lab work doesn't care about simulations. At some point, you have to pipette actual liquid, run the assay, and see if reality agrees with the code. And then you have a lack of medical intuition, AI hallucinations, equipment translation errors, compliance and safety boundaries, and biased insights.

Many challenges - and they all basically spell out the same thing: labs (still) need humans. Which is why we were honored to be featured in the latest edition of MLO’s fantastic magazine - and specifically on the most suitable article possible - the one about AI in LIS - because this is exactly what we do.

If AI is forced to “talk” to clunky, thirty-year-old lab software that can barely export a clean CSV, it’s basically useless. If clinical labs want AI to track samples and close the lab loop, they need modern lab infrastructure that actually connects the physical world to digital intelligence. Claude may be the smartest AI tool of them all - but even he (she? they?) can't do a whole lot if the LIS isn't talking the same language.

What do you think? Can legacy LIS systems catch up…?

05/10/2026

Things we’ve learned this week from talking to lab directors, #418:

Tech stack continues to fail lab staff on a daily basis, because they still have to leave their primary workflow to check a lab result.

Oh, the frustration.

When evaluating a modern SaaS lab platform, the bar shouldn't just be "it connects." No, the bar must be set at “how fast that data actually becomes actionable”.
And how do you do that? That’s actually the easy part!

Does the platform offer true, real-time sync in milliseconds? Does it also offer direct EHR/portal embedding with zero duplicate logins? Can the vendor prove the platform has smart auto-alerting triggered?

Any cloud-based LIS platform that doesn't offer these basic capabilities is basically just another good-looking variation of a legacy LIS system. Today’s clinical lab reality is very simple - diagnostic data has zero value until the person who needs it can see it.

We elaborate in depth here: https://eu1.hubs.ly/H0ywLFx0

Cloud-based LIS platforms that were built by lab people for lab people are the only ones that acutely deliver the core value. To cut out the friction and stop the portal-hopping, you need a platform that works for you, not the other way around.

So, tell us - what’s your biggest lab hurdle that slows your result delivery?

01/10/2026

We are officially finalists for the Lab Awards 2026, nominated for the Best Automation & Data Innovation award. Hold on! We haven’t won yet 😊

But as they say in Hollywood, it’s an honor just being nominated… And honestly? Being shortlisted for this specific category means a lot.

Clinical labs are under insane pressure. They've always been. Our entire focus is stripping away the manual workloads, eliminating operational bottlenecks, making data actually work for the teams running the show - and not the other way around.

Simply put - we’re doing what we’re doing because labs deserve better - and being recognized for that proves we're focused on the right fight.

Huge credit to our entire team for building the engine, and to the labs trusting us to run it.

Fingers crossed for the final results - but now, put down that Drink, Bob; we need to get back to work.

28/09/2026

If there’s one thing every clinical lab director dreams about (other than wishing their dashboards would work for them and not vice versa), it’s that MDs and physicians will be their trusted partners.

But in reality, physicians and lab directors often find themselves at odds, for no good reason.

The reason for that is quite simple, and frustrating - for both sides: most of the “remote access" tools in diagnostics were built to tick the IT boxes rather than fit how a physician actually practices. Many LIS vendors will claim they provide future-grade connectivity, when in reality they offer the same old portal fatigue, fragmented logins, and slow access to critical data.

So how can you - as lab directors- work alongside the MDs while doing your best day-to-day lab work?

* Ditch the portal obstacle course - there’s really no reason to perform three separate logins and five clicks through a legacy UI.

* Understand their reality - the technological partnership you’re both seeking is rooted in personalized workflows that integrate cleanly.

* Turn data into actionable clarity - Fast results. Frictionless context. Seamless communication. Proactive updates.

The physician/lab partnership is a constant roadblock in healthcare. But it doesn't have to be. Alongside 4 other common failures that can and should be avoided, we’ve gathered everything you need to know about solving the challenges with a personalized lab cheat sheet - and it’s wrapped nicely in this guide: https://eu1.hubs.ly/H0yw51K0

No bow. Just data and best practices 🙂

And if you didn't find the right challenge and solution in our guide, let us know: What is the biggest point of friction in your current physician outreach workflow?

25/09/2026

Ladies and gentlemen, we are gathered here today to defend the analyzer. Stop blaming the analyzer! The analyzer was never the whole workflow - and optimizing one perfect step in a broken process still leaves your lab with a broken process.

In the life of a clinical specimen, there are many handoffs, and every handoff is another opportunity for something very human-error-oriented to happen. Meanwhile, that innocent analyzer is happily doing exactly what it was designed to do. So, perhaps we’ve been looking for diagnostic risk in the wrong place…?

Check out our full breakdown:
https://eu1.hubs.ly/H0yd7Rc0

And for heaven’s sake, leave Britney alone!

Yes, some of us refer to analyzers as Britney or Christina. Don't judge us, please.

22/09/2026

How can a lab result be technically ready - but still be clinically late? Well, guess what - that happens more often than people think, and this is the typical way it happens:

An order starts in the physician’s system → the lab receives part of it → someone fills in what’s missing → a change is made upstream but doesn’t make it downstream → the specimen arrives before the information does → somebody picks up the phone.

Meanwhile, everyone can technically say the systems are “integrated.”

The result? Chaos. On a daily basis. The kind of chaos you learn to live with. But do you really have to?

But the thing is, none of these steps look catastrophic on their own. It’s only when you put them together that you get hours of friction around a test that probably should have taken minutes to run.

The real problem with separate healthcare systems is not a technical challenge like the AI GPTs tell you (when you’re frustrated and searching for a solution to your lab’s lack of connectivity and efficiency). No, the real problem is that disconnected lab systems force people to compensate for what the technology doesn’t understand.

Basically, people become the middleware:

They re-enter demographics, reconcile orders, chase missing information, and constantly check for updates. They are forced to do tedious tasks, and every manual handoff adds time and creates more opportunities to get something wrong.

That's why we should judge interoperability in clinical lab workflows by workflow, not by interfaces. The LIS architecture should make the correct clinical path the easiest path - and that means your LIS will work for you, instead of you and your staff wasting half your days working for the LIS.

Prove us wrong.

Labos

22/10/2026

19/10/2026

16/10/2026

13/10/2026

07/10/2026

05/10/2026

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28/09/2026

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