u/Lav_Dave

UK FCA launched theirs in 2016. Singapore, UAE, India followed. Nearly every major market has one now.

Eight years in I keep asking the same question - have they actually delivered?

Genuinely think they've created something valuable that didn't exist before - a real conversation between regulators and builders. Testing without full compliance cost lowers the barrier for smaller players. Some real products came through these programs.

But the honest criticism is fair too.

The gap between "sandbox graduate" and "actually licensed and operating at scale" is still huge in most markets. Some programs the graduation rate looks great on paper but very few actually launch commercially after.

And sometimes it just slows you down. Twelve to eighteen months structuring your product to fit sandbox criteria is time you're not spending building and selling.

The access question bothers me most though. In practice these programs favor companies that can afford the legal and compliance expertise to navigate the application. Which might not be the most innovative ones.

Genuine accelerator or mostly regulatory optics? Curious what people who've actually been through one think.

UK FCA launched theirs in 2016. Singapore, UAE, India followed. Nearly every major market has one now.

Eight years in I keep asking the same question - have they actually delivered?

Genuinely think they've created something valuable that didn't exist before - a real conversation between regulators and builders. Testing without full compliance cost lowers the barrier for smaller players. Some real products came through these programs.

But the honest criticism is fair too.

The gap between "sandbox graduate" and "actually licensed and operating at scale" is still huge in most markets. Some programs the graduation rate looks great on paper but very few actually launch commercially after.

And sometimes it just slows you down. Twelve to eighteen months structuring your product to fit sandbox criteria is time you're not spending building and selling.

The access question bothers me most though. In practice these programs favor companies that can afford the legal and compliance expertise to navigate the application. Which might not be the most innovative ones.

Genuine accelerator or mostly regulatory optics? Curious what people who've actually been through one think.

21st Century Cures Act made interoperability a legal requirement. Every major vendor claims they support it.

And yet here we are.

The technology isn't really the problem anymore - FHIR R4 is solid, APIs exist. The problems are incentive structures and implementation complexity.

What actually breaks in practice:

Vendor data models that technically "support" FHIR but make clean extraction nearly impossible. Patient matching across different systems is harder than anyone admits. Consent rules vary by state and add another layer of complexity. And 90% of the real clinical information is still buried in free text notes that don't transfer meaningfully anywhere.

There are genuine bright spots - patient access apps using FHIR are actually working, Epic and Cerner have improved APIs under regulatory pressure, and TEFCA is building a real national framework.

But the gap between "we support interoperability" and actually using a patient's data from another system in your daily workflow is still massive at most hospitals.

What's the most frustrating interoperability gap you deal with day to day?

Sat through another predictive maintenance demo last week. Clean dashboards, instant alerts, beautiful failure predictions.

What they didn't show was the 18 months of unglamorous work before any of that becomes real.

From what I've seen it actually goes like this:

First you spend 6-12 months just getting data. Sensors on equipment, wrestling data out of legacy PLCs that were never designed to share anything, building connectivity infrastructure. Most people massively underestimate this part.

Then another 3-6 months figuring out what "normal" even looks like. Raw sensor data is noisy and messy. You can't detect abnormal until you really understand normal across different loads, seasons and operating conditions.

Then you actually build the model - which is where vendors start their demo. Vibration analysis on rotating equipment is usually where I'd start. Motors, pumps, gearboxes. Well understood failure modes.

Then you connect it to something useful. A prediction that nobody acts on is worthless. Getting it into your CMMS and maintenance scheduling is where the ROI actually shows up.

Honest timeline: 18-30 months before you have reliable predictions on even a subset of critical assets.

Where are you in this process? What phase nearly killed the project for you?

Sat through another predictive maintenance demo last week. Clean dashboards, instant alerts, beautiful failure predictions.

What they didn't show was the 18 months of unglamorous work before any of that becomes real.

From what I've seen it actually goes like this:

First you spend 6-12 months just getting data. Sensors on equipment, wrestling data out of legacy PLCs that were never designed to share anything, building connectivity infrastructure. Most people massively underestimate this part.

Then another 3-6 months figuring out what "normal" even looks like. Raw sensor data is noisy and messy. You can't detect abnormal until you really understand normal across different loads, seasons and operating conditions.

Then you actually build the model - which is where vendors start their demo. Vibration analysis on rotating equipment is usually where I'd start. Motors, pumps, gearboxes. Well understood failure modes.

Then you connect it to something useful. A prediction that nobody acts on is worthless. Getting it into your CMMS and maintenance scheduling is where the ROI actually shows up.

Honest timeline: 18-30 months before you have reliable predictions on even a subset of critical assets.

Where are you in this process? What phase nearly killed the project for you?

Sat through another predictive maintenance demo last week. Clean dashboards, instant alerts, beautiful failure predictions.

What they didn't show was the 18 months of unglamorous work before any of that becomes real.

From what I've seen it actually goes like this:

First you spend 6-12 months just getting data. Sensors on equipment, wrestling data out of legacy PLCs that were never designed to share anything, building connectivity infrastructure. Most people massively underestimate this part.

Then another 3-6 months figuring out what "normal" even looks like. Raw sensor data is noisy and messy. You can't detect abnormal until you really understand normal across different loads, seasons and operating conditions.

Then you actually build the model - which is where vendors start their demo. Vibration analysis on rotating equipment is usually where I'd start. Motors, pumps, gearboxes. Well understood failure modes.

Then you connect it to something useful. A prediction that nobody acts on is worthless. Getting it into your CMMS and maintenance scheduling is where the ROI actually shows up.

Honest timeline: 18-30 months before you have reliable predictions on even a subset of critical assets.

Where are you in this process? What phase nearly killed the project for you?

Every demo makes it look easy. Clean dashboards, instant alerts, magic predictions.

Nobody shows you the 18 months of groundwork before any of that works.

Here's what it actually looks like:

First you need data - sensors on equipment, getting legacy PLCs to share data they weren't designed to share, building connectivity from scratch. This phase alone takes 6-12 months and most people massively underestimate it.

Then you need clean data - raw sensor readings are noisy and inconsistent. You need to know what "normal" looks like across different loads, conditions and seasons before any model can spot "abnormal." Another 3-6 months minimum.

Then the model - this is where vendors start their demo. Vibration analysis on rotating equipment is usually the best starting point - motors, pumps, gearboxes. Well understood failure modes, detectable signatures.

Then integration - a prediction nobody acts on is worthless. Connecting it to your CMMS, maintenance scheduling and parts inventory is where the actual ROI lives.

Realistic timeline for meaningful predictive maintenance on even a subset of critical assets: 18-30 months.

Where are you in this journey? What phase has been the hardest to get through?