Labos

Labos LabOS is Next Generation LIS that supports healthcare providers' digital transformation worldwide.

Picture this - healthcare AI makes a mistake. It harms a patient. Who’s going to pay for it? Now consider this - most o...
25/06/2026

Picture this - healthcare AI makes a mistake. It harms a patient. Who’s going to pay for it?

Now consider this - most organizations deploying AI tools in healthcare right now can't answer that cleanly.

Can’t? Won’t? That’s a question, and that’s also the reason why the article in the comments is worth your time. Among other claims, it raises the question about AI, which is already running deep inside clinical work. AI schedules, dispenses, performs diagnostics - but the rules meant to govern it are still being written.

However, the point that stuck with us, as LIS vendors, was that the real test of a healthcare AI tool shows up in the contract, long after the demo is over. Indemnification, audit rights, and a clear answer to accountability when a model makes a call that affects a patient. Those clauses say more than any feature list. And most LIS vendors can’t give proper answers.

Honestly?

If we were running a lab, our first question to any LIS vendor would be, “Are you training your models on my patients' data, and what happens to that data?”

Any lab that treats this as a board-level risk today will be glad they did. The ones treating it as paperwork won't. Trust us, we’re an LIS vendor, and we use AI wisely.

Anyway, check out the article in the comments, and if you have any questions, we’re here. Worth a read.

The D2C lab testing boom has hit a major roadblock: doctor frustration - according to the article in the 1st comment. In...
22/06/2026

The D2C lab testing boom has hit a major roadblock: doctor frustration - according to the article in the 1st comment.

In a nutshell, patients are ordering their own screenings online, but when complex results come back, they drop raw data into their doctor's lap, demanding immediate interpretation.

This leaves the MDs playing catch-up, managing patient anxiety, and dealing with fragmented data. And honestly…? You can't blame patients for wanting autonomy, and you can't blame MDs for being overwhelmed.

Because the actual problem is the lack of a bridge - and the solution is not stopping the flow of patient data, but rather contextualizing the data before it breaks the MD-patient relationship. The way we see it, what MDs and medical labs really need is to track cumulative trends, flag true abnormalities like delta shifts, and manage patient communications in one synchronized dashboard.

After you’re done reading the original article that flagged the problem, let us know - do you have another solution? Is your lab handling the MD-patient overload well?

The silent killer for medical labs isn't technology, no matter what we or anyone else says. No, what really puts medical...
19/06/2026

The silent killer for medical labs isn't technology, no matter what we or anyone else says. No, what really puts medical labs at risk is the burnout crisis among the staff.

3 in 4 lab workers report they lack the resources needed to handle their workload. And they’re not talking about incubators, sterilizers, or centrifuges. They’re talking about critical system infrastructure.

Check this out to learn more: https://eu1.hubs.ly/H0v-zXm0

The promise of AI-driven precision blood testing sounds incredible: running hundreds of biomarkers from a single sample ...
17/06/2026

The promise of AI-driven precision blood testing sounds incredible: running hundreds of biomarkers from a single sample to phase out repetitive panels.

Find the article that promises just that in the first comment - and then, think about the massive ex*****on gap that no one is talking about: an advanced AI model can identify 200 biomarkers simultaneously - but what happens when that complex data hits a legacy LIS system?

Yep. It chokes.

Many clinical labs are running on architectures built decades ago, designed for simple, linear results. You cannot unlock the financial or clinical value of next-generation diagnostics if your core system treats advanced data like a foreign language.

Because the bottleneck is (and always will be) the operational pipes. Not AI models that are messing up your systems, and not the phlebotomist who ran late, or any other excuse your legacy LIS vendor may conjure up.

When advanced diagnostics arrive at your lab, your LIS can actually understand the data and automate the workflow. It’s all about the cloud-native infrastructure that was designed for this specific shift, and any other technology-based market changes.

And what about your lab? Is your LIS software ready to ingest next-gen multiplex data, or is infrastructure holding your science back? Food for thought. Let us know in the comments. Perhaps we can come up with a better solution moving forward.

Today is World Blood Donor Day. A single donation can save 3 lives - but only if the logistics machine behind it works f...
14/06/2026

Today is World Blood Donor Day. A single donation can save 3 lives - but only if the logistics machine behind it works flawlessly.

Behind every blood draw is a high-stakes race against time: complex screening, temperature tracking, and rapid cross-matching. When supplies are low, any friction in the lab workflow is way more dramatic than an operational headache. It's a direct threat to patient care.

A modern blood supply chain simply can’t rely on rigid, legacy software. If your system can't track components seamlessly and automate safety logic on the fly, the entire lifeline is bottlenecked. What can you do about it for your lab? Check out the link in the comments. That’s a good place to start.

Thank you to everyone who donates. And to the lab professionals managing the supply chain under pressure - we see and salute you.

You’re looking at this image and are probably thinking - “yeah, this is yet another social post about AI”. And to some e...
11/06/2026

You’re looking at this image and are probably thinking - “yeah, this is yet another social post about AI”. And to some extent, you’re right. But this post is going to be about anxiety.

Which is what most lab professionals feel, day to day, because of AI. But, let’s put the hype aside - what are the risks? What are the questions?

Can AI Make the LIS Smarter? Can AI Help Test Results Tell Stories? Are we over the AI hallucinations era?

Well, yes, yes, and probably not. In fact, we’re not sure we’ll ever get past the hallucinations phase. Because the truth is, it doesn't really matter how you look at the AI revolution and the challenges it gave birth to. And no, it doesn't really matter if your LIS can integrate AI properly or not (it probably can’t, and in that case, let’s talk; see the link in the comments).

The one thing you need to remember when it comes to AI in clinical labs is that you, the lab professional, are the one in charge.

What we really need are guardrails, and not just innovation. The labs that succeed with AI won’t be the ones that implement it fastest, but the ones that implement it thoughtfully. That means validation protocols, regular audits, clear documentation, and if you want to get the whole picture and the full breakdown, check out our new article right here:

https://eu1.hubs.ly/H0v-phC0

What do you think? Are we the guardians or the clients? Is AI selling us dreams and hopes?

The 2026 forecast for clinical labs is a masterclass in contradiction. You’ll find it in the comments, but here’s the bo...
08/06/2026

The 2026 forecast for clinical labs is a masterclass in contradiction. You’ll find it in the comments, but here’s the bottom line:

Brace for heavy Medicare reimbursement cuts under PAMA (Protecting Access to Medicare Act of 2014), but make sure you invest six figures (!!) into digital pathology and AI.

The message is clear: Do much much more, with so much less. As Doctor Evil says… “Righhhhht”.

Can you really innovate your way out of a margin squeeze if your infrastructure is anchoring you to the past? No, you can’t, because adding flashy AI tools on top of legacy systems is like putting a spoiler on a car with a broken engine. It doesn't fix the core problem.

If your software can't automate routine logic, adapt to regulatory shifts on the fly, and protect margins at the workflow level, the macro trends will win. That’s why survival this year (not to mention succeeding) isn't about chasing every tech trend.

It’s about building a modern, cloud-native operational foundation, with clinical engines that keep labs resilient, compliant, and profitable - no matter what the market throws at them next.

How is your lab balancing the pressure to modernize against tightening margins?

Don't be this guy. Nothing should shock you about the medical lab ecosystem. But just in case some things may still shak...
04/06/2026

Don't be this guy.

Nothing should shock you about the medical lab ecosystem.

But just in case some things may still shake you up, we put together the ultimate LIS cheat sheet: once you’re done with this read, you won't ignore the hidden failures in your LIS anymore - because this is the ultimate cheat sheet for efficiency.

Get it right here: https://eu1.hubs.ly/H0vBtsw0 and uncover best practices, tips, real-world scenarios, and use cases, from over 30+ of LIS field experience.

Because, honestly? You deserve better.

Quality culture is real - but it’s not enough for medical labs. We came across a sharp piece in Lab Manager on building ...
01/06/2026

Quality culture is real - but it’s not enough for medical labs.

We came across a sharp piece in Lab Manager on building a lab where quality and operations stop fighting. The argument, basically, is right: treat quality as part of operations, not an admin burden, and the whole lab gets stronger.

Example? One team cut a 135-page quality manual to 35, then passed back-to-back audits with zero findings.

Sounds amazing, but the article left out the part that makes the culture stick…

Quality feels like "extra work" because the LIS treats it that way. When QC and documentation are bolt-on steps, everyone is faced with a choice between "get the sample out" and "dot the I's." And as we all know, under pressure, people pick speed. To get the job done as fast as possible.

That's not a culture failure - it's a systems failure, all dressed up in a culture costume.

The way we see it, the leadership sets the vision; the LIS keeps it real when the lab is at full capacity. Get your leaders aligned - build quality into the workflow, and let your (not legacy) LIS do its magic and turn “the right thing” into what your lab deserves: the easy thing.

What do you think?

Medical labs are currently operating in an amazing landscape, and the crazy thing is that most of them aren't even fully...
28/05/2026

Medical labs are currently operating in an amazing landscape, and the crazy thing is that most of them aren't even fully aware of it.

Crazy, from a positive perspective, yeah?

This is the time of a fundamental shift, moving from the era of the System of Record (passive storage) to the era of the System of Action (active intelligence). To truly grasp the meaning of the dramatic shift, one must first dig deep into the history of the laboratory information and management systems - and only then, the future becomes clearer.

Luckily for you, after 30+ years in the healthcare industry, our team has watched this evolution firsthand - and documented every twist, mistake, and breakthrough.

And this is what we came up with: https://eu1.hubs.ly/H0vBrLy0

Download our new (and free) eBook to:

* Understand the architectural decisions - good and bad - that shaped today's LIS landscape.
* Learn how labs transformed from passive record-keepers to active intelligence hubs.
* Prepare your lab for AI and automation with a clear historical context.
* Get practical tips and best practices to turn your lab into a powerhouse.

Did we miss anything? Are our predictions wrong, or did we get everything spot on? Don't forget to let us know what you thought!

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