Most Canadian SMBs aren’t on their first software tool for the job, they’re on their third. SaaS economics work when you’re selling one product to a million customers with similar needs; the problem is that most Canadian SMBs don’t have similar needs. AI tooling has shifted the math: a small embedded engineering team can now deliver custom software cost-competitive with the SaaS stack a business is already paying for. The Canadian SMBs moving fastest aren’t tech-native startups, they’re nonprofits, Indigenous-owned organizations, trades and energy service companies, and founder-owned businesses that SaaS consistently underserved.
Canadian SMBs aren’t on their first software tool for the job. They’re likely on their third. Not because they kept making bad decisions, the first two just almost worked. Close enough to buy, not close enough to actually run the business on. So another one gets added, workarounds get built, staff get trained on the gap between how the software works and how things actually get done. The feature request that would have fixed the real problem, submitted eighteen months ago, is still sitting in someone’s backlog marked “under consideration.”
SaaS was built to scale. Your business wasn’t built to fit it.
SaaS economics work when you’re selling one product to a million customers with roughly similar needs. The whole model depends on it. A platform that works well for most of its users is a successful platform, even if it works poorly for the rest.
The problem is that most Canadian SMBs don’t have roughly similar needs:
- A nonprofit managing a complex web of funders, programs, and frontline staff doesn’t run like a B2B sales team, even if both are technically “tracking relationships”
- An Indigenous-owned organization delivering community services has governance requirements and stakeholder dynamics that no off-the-shelf platform was designed around
- A trades company tracking job costing, field crews, subcontractors, and inspections needs a workflow that most project-management platforms approximate but never actually nail
So Canadian SMBs adapt. They build workarounds. They export to spreadsheets. They train staff on the gap between how the software works and how the business actually runs. And every year at renewal, they ask themselves whether there’s something better out there — and usually discover there’s just something different.
The CTO-and-agency path has its own problems
The obvious alternative is to build your own software. Hire a CTO, bring on a development team or agency, get something built that actually fits.
This works, sometimes. But the failure modes are consistent enough that they’re worth naming.
A CTO hire takes months to find and months more to onboard. By the time there’s a plan, six months have passed and you’re facing a build-or-buy decision all over again, this time with more overhead. If you go the agency route, you get a project. The agency delivers, moves on, and the code works until it doesn’t, at which point you’re looking for someone new who can make sense of what someone else built. They never truly understood your business, just the specs you handed over. Without being embedded in how the business actually runs, specs only get you so far. (The full fractional-vs-agency breakdown is in our companion article.)
The accountability gap is another issue. The fractional CTO takes another engagement. The agency is three clients down the road. Even the internal team loses key people to better offers, as internal teams do. What’s left is a technology investment that’s harder to maintain than it was to build, owned by a Canadian SMB that never quite had the internal capability to own it.
None of this is anyone’s fault, exactly. It’s what happens when an ongoing business need gets solved with a one-time project. Software is never really done. It needs to grow as the business grows, adapt as requirements change. Treating it as a deliverable rather than a capability is where most of these engagements eventually fall apart.
What AI has actually changed for Canadian SMBs (and it’s not what most people think)
Most of the conversation about AI in business has been about automation, what tasks it can replace, what jobs it might eliminate, what processes it can speed up. That’s a real conversation. But there’s a quieter shift happening that matters more for Canadian SMBs.
AI has fundamentally changed the economics of building software.
A small team of skilled product engineers working with the right AI tooling can now produce what previously required a much larger group. The research, the prototype, the testing infrastructure, the documentation, significant portions of what once consumed engineering time can now be handled differently, faster, with fewer people. This isn’t a marginal efficiency gain. It’s a structural change in what a lean team can deliver.
The old model had a lot of layers between the person with the problem and the person writing the code, client to sales, sales to product, product to design, design to engineering, engineering to QA, and back again, something getting lost or distorted at every handoff. The product engineer model collapses that chain.
The practical implication: for the first time, custom software built specifically for your business can be cost-competitive with the SaaS subscriptions you’re already paying. Not for everyone. Not for every use case. But for a meaningful slice of Canadian SMBs that have specific needs and have been settling for general solutions, the math has shifted.
The model that’s emerging, embedded engineering for Canadian SMBs
What we’re seeing — and what will become much more common over the next few years — is the embedded engineering team.
The idea is straightforward: instead of a one-time project or a full-time hire, a Canadian SMB brings on an external team that operates like an internal engineering department. They learn the business. They’re in the planning conversations. They understand not just what needs to be built but why, and what will need to change six months from now.
The accountability works differently than the agency model because the relationship doesn’t end at delivery. The team is measured on outcomes that evolve as the business does. When something breaks, they fix it. When the business adds a service line or enters a new market, the software adapts. The HR headache, hiring, managing, losing people, rehiring, stays off the business owner’s plate. The ability to scale up and down removes the ongoing staffing line item from the balance sheet entirely.
This isn’t a new concept in theory. What’s new is that AI tooling has made it economically viable for Canadian SMBs that aren’t enterprise-sized. A lean embedded team can now deliver at a level that previously required a much larger internal department. (For a deeper look at the model itself, see our DDaaS vs Fractional CTO comparison.)
Who’s actually doing this
The Canadian SMBs moving to this model fastest are not, in our experience, the tech-native startups. They already have engineering teams. The ones moving fastest are the businesses that SaaS consistently underserved:
- Nonprofits building donor acquisition and program management tools that reflect how they actually operate, not a generic platform built for a different industry
- Indigenous-owned organizations creating digital infrastructure on their own terms, with software that fits their governance structures and community relationships rather than forcing those relationships into categories designed for corporate sales pipelines
- Trades and energy service companies building job costing, crew management, and compliance tracking systems that the major platforms approximate but miss on the details
- Founder-owned businesses scaling past the point where spreadsheets and workarounds hold up
These aren’t tech companies. They’re Canadian SMBs that got to a point where the cost of using the wrong tools became more visible than the cost of building the right ones.
Four questions worth asking before your next renewal
We’re not suggesting every Canadian SMB should abandon its SaaS stack. For plenty of businesses, the right off-the-shelf tool still makes more sense than building something custom. But the decision deserves a more honest look than most businesses give it at renewal time.
- How much of your current stack is actually used as intended? If your team has built workarounds for a significant chunk of a tool’s core functionality, it probably wasn’t designed for your use case.
- What does your tech stack actually cost, fully loaded? Add the subscriptions, the implementation time, the training, the manual work that fills the gaps, and the productivity drag from software that doesn’t quite fit. The number is usually larger than the invoice.
- What would change if the software actually fit? Not the software you have, software built around how your business runs. If the answer is material, the economics of custom development have probably shifted enough to be worth a real conversation.
- Is this a one-time problem or an ongoing one? If your business is growing, changing, adding services, entering new markets. You need a capability that evolves with you, not a project that ends.
The SaaS cycle isn’t going away. For a lot of businesses, it’s still the right answer. But for a growing number of Canadian SMBs, the ones with specific needs, the ones that have been adapting to software instead of the other way around, the calculus is changing.
The next renewal cycle is a reasonable time to ask whether you’re signing up for another year of almost, or whether something else has become genuinely viable. A 15-minute conversation is usually enough to figure out which side of that line your business actually sits on.
Related work: See our operational systems work or grant-funded builds.
Common questions
Why are Canadian SMBs typically on their third SaaS tool for the same job?
Not bad decision-making, the first two tools almost worked. Close enough to buy, not close enough to actually run the business on. So another gets added, workarounds get built, staff get trained on the gap between how the software works and how things actually get done. The pattern is structural: SaaS is designed for the median customer in a category, and most Canadian SMBs aren’t the median customer in any category.
Is custom software now actually cheaper than SaaS for Canadian SMBs?
For a meaningful slice of Canadian SMBs with specific needs, yes, AI tooling has changed the economics. A lean embedded engineering team can now deliver custom software cost-competitive with the SaaS subscriptions a business is already paying. Not for every use case. But when the fully-loaded SaaS cost (subscriptions + implementation + training + workarounds + productivity drag) is honestly tallied, the break-even point on custom development is much closer than most businesses assume.
What’s the difference between hiring an agency and using an embedded engineering team?
Agencies operate on a project basis, scoped work, defined endpoint, then exit. Embedded engineering teams (DDaaS) operate as an ongoing department, same team, learning the business over months and years, accountable for outcomes that evolve with the business rather than deliverables tied to a contract. The accountability model is the structural difference: agencies own deliverables; embedded teams own outcomes.
Which Canadian SMBs benefit most from moving off SaaS?
The ones SaaS underserved structurally: nonprofits with complex funder/program/frontline-staff dynamics, Indigenous-owned organizations with specific governance requirements, trades and energy service companies with job-costing and crew-management needs that platforms approximate but never nail, and founder-owned businesses with workflows built around how they actually operate rather than how a SaaS vendor designed for them to operate.
Should every Canadian SMB build custom software?
No. For plenty of Canadian SMBs, the right off-the-shelf SaaS tool still makes more sense than building something custom. The point isn’t that SaaS is wrong, it’s that the build-vs-buy decision deserves a more honest look at renewal than most businesses give it. The four questions in this article (workarounds count, fully-loaded cost, what-would-change-if-it-fit, ongoing-vs-one-time) are a starting framework.
