u/rdbmas

I read the NVIDIA developer docs for HALOS and marvel how they effectively locked in a MOAT with a safety ecosystem. They align it to what industry expected and capitalized.

Physical AI Architecture (Neutral and Halos Compare)

Then i asked three pointed qtns.
-What leads to a mandate of a Safety Ecosystem Architecture
-can we deduce which industries and what physical AI outcomes truly need a safety RTOS.
-who are the next vendors set to replicate something like HALOS. More importantly, where is QNX likely expected to attach next.

We begin by understanding Deloitte's mapping of 40+ use cases that confirms Physical AI spanning manufacturing, mobility, healthcare, energy, retail, and defense as distinct verticals, not robotics variants. (a current $383 Billion to $3.63 Trillion growth forecast by 2032-34).

We then narrow down those use cases of Physical AI where safety RTOS is a must. That distinction is made because the market conflates "AI that touches physical infrastructure" with "AI that must be functionally safe," but only the latter category actually creates the RTOS/SIL certification demand (i.e where you would want QNX by your side).

We correlate those specific use cases and map against the silicon providers that are attached/working on it. What other chip providers can we see? Who are the potential RTOS partners aligned/can be aligned.

UseCase > Silicon Vendor Mapping

The market has moved into "compute-heavy AI silicon" players and "MCU-grade deterministic safety silicon" players, and almost every Physical AI use case actually needs both working together in a mixed-criticality architecture.

In short:
An MCU (Micro controller Unit) is designed for predictability, not throughput, it runs simple control loops (read sensor, apply logic, drive actuator) in microseconds with guaranteed, repeatable timing.

NVIDIA's and the likes. That's optimized for massive parallel throughput to run neural networks and complex workloads.

And what's the pt of all this?
You have Silicon providers heading towards two paths of Physical AI outcomes against distinct use cases where safety is mandated.

And then there's the second-order consequence. As regulatory scrutiny tightens, expect further vertical consolidation where AI-silicon vendors acquire or deepen exclusive ties with certified RTOS vendors, turning what is currently a partnership ecosystem into owned, closed-loop supply chains.

QNX's certification pedigree (IEC 61508, ISO 26262, IEC 62304, up to SIL 3/ASIL D) is treated as a reusable trust asset that would take a competitor a decade to replicate independently.

So if you're a chip vendor and want to capture this Trillion dollar market opportunity. Which RTOS would you pick?

The winning pattern is a chip vendor plus RTOS vendor duopoly.

Analysts, it's time to connect the dots.

so we are all following along what QNX is doing on the Automotive and Robotics space.
Let's have analysts catch up on that at some pt.

Incidentally on Robotics, we've seen the NVIDIA Halos Ecosystem announcement. I think there's something more to be unraveled on Toradex + QNX + NXP i.MX95 Ecosystem.
Maybe someone knows more about this and can shed more insights.

Anyway, I was curious on whats happening in other segments, particularly...military.

Reading the threads on how BB is a Canadian company and won't necessarily have access to US military contracts. That Blackberry history has privileges and also the reason why QNX operates inside the US defense ecosystem with the access profile of a domestic US supplier. (70 years of defense integration bet US and Canada helps as well)

And if we look at certification standards in the US military. There's a prominent 10 Certifications that holds the hierarchy/framework the US maintains. If we look at RTOS and who tends to be stacked favorably against the 10. There's 4-5 that come up top.

What's interesting is QNX SDP 7.1 achieved FACE (Future Airborne Capability Environment) in 2022. Hence IMO, it doesn't mean they are applicable only to land/automotive outcomes in the military.

RTOS Scoring against 10 -standard Cert Framework

And if we infer some more on what the next big thing in military. You tend to hear alot about Anduril Lattice. In short a OS/platform allowing the operator to Command and Control multiple systems.

And consolidating sources for military establishments committed to LATTICE

Defense Commit on LATTICE

There are some traces of QNX RTOS inclusion but not definitively traceable so keen to get POVs from others on here.

Is there a potential military partnership in play with Anduril.

I've watched a few of JW's videos and he strikes me as patient, focused and calculated.
The kind of leader that takes meticulous time with an engine so it sounds the way he wants it to.

i've read some of the posts in the forum about long term/5 year time frames to see this stock pop. We're missing a key indicator that shows QNX revenue coming in almost like a well oiled engine.

Royalty backlogs convert to revenue typically in a 2-3 year cycle.
Just inferring some of the earnings, it's running 2 years bet 34-49%

Backlog → Revenue at 2-Year Lag

if you look at QNX revenue and compare with the work done on the platform and raising awareness. It shows JW at the helm tuning that engine. Especially how QNX Everywhere was a key pt.

QNX Annual revenue and Platform Versions

which leads to the FY28 -FY30 Harvest

The implication looking forward is by no means a guaranteed prediction but one can gauge:
-FY26 backlog = ~$950M → FY28 projected revenue: $323–$365M (at 34–38% conversion)
-FY27 backlog = ~$1.05B (if additions continue outpacing recognition) → FY29 projected revenue: $357–$400M

Now here's the part that just boggles the mind. The current surge is attributed to Automotive mostly.

QNX revenue typically is expected to generate across the below key streams:
-Automotive
-GEM: Robotics
-GEM: Medical
-GEM: Industrial
-Alloy Kore

In the earnings call, JG captured GEM could be larger than automotive.
So what happens when GEM comes in along with Alloy Core. Automotive is now the floor, not the ceiling.

That puts QNX on a path from $304M to $434M–$783M by FY30, with the upper bound of that range requiring not automotive outperformance, but GEM and Alloy Core converting at rates already consistent with the pipeline, management has publicly confirmed.

So yeah.....patient, focused,calculated.

i listened to the Q1,FY27 earnings. Analyst can do better.
Lets provide some color (pun intended). This is more for discussion and NFA.

I went through a few Quarters to infer and made some deductions:
My points of focus.
-what verticals in physical AI have QNX penetrated (besides Auto and Robotics)
-the QNX backlog, can a % breakup be deduced.
-development licenses growth that reveal an indicator to deploy QNX and serve as a Royalty Prediction Engine.

There was a previous analyst write up that talked about AI heart pumps and that really made me curious. In short, where is Physical AI emerging across the sectors and where QNX is revealing itself.

QNX - Physical AI Sector Insertion

BB does not publicly segment the backlog by verticals but just inferring some % breakup from previous earnings presentations.

Making some assumptions:

QNX backlog at ~$1B across sectors

Finally, software is only as good as the people who can actually deploy it well. Developers have to learn, work with it and embed it onto hardware. When an OEM buys QNX development tools and seats, they have made a committed decision to build a product on QNX. That decision precedes mass production and therefore royalty revenue.

QNX Dev License Growth

This is by no means an accurate depiction of the OEMs that contributed to the uptake in Q1, FY27 but more a confidence level % based on deducing press releases. In short, i don't think we have seen the NVIDIA Halos relationship kick in yet.

Q1, FY27 Dev License Surge -Deduced OEMs by Confidence

If you look at some of this AI stocks that have taken off.
a pattern of sorts runs true. (this is for fun and NFA)

1st tier of revelation: UBS, Barclays, RBC, Susquehanna, Benchmark, Bernstein, Wells Fargo, Stifel, CIBC, TD Cowen, Baird.

2nd tier : Jefferies, Goldman, BofA, Wedbush, Cantor.

3rd tier and the ones that bring it all home : Citi and Morgan Stanley.