Most companies between 50 and 100 employees are spending somewhere between $450K and $1M a year on SaaS subscriptions. We know because we’ve looked at the numbers.
The stack usually goes something like this: a CRM that’s too big for the team. A project management tool nobody fully adopted. Three different reporting dashboards that don’t talk to each other. A handful of Zapier automations holding it all together with duct tape. And a growing line item for “integration middleware” that nobody budgeted for.
Every tool made sense when it was purchased. But stacked together, they create a slow, expensive, fragile system that no single person understands end-to-end.
We think there’s a better model. We call it Service as Software.
The idea in one sentence
Instead of renting someone else’s software and bending your business to fit it, you pay once to have software built around how your business actually works, and you own it.
How this plays out in practice
One of our recent clients, a mid-size professional services firm with about 70 people, was paying roughly $387K per year across 11 SaaS subscriptions. Their CRM, project tracker, time-tracking tool, invoicing system, and client portal were all separate products from separate vendors, connected by a maze of Zapier workflows and manual CSV exports.
We built them a single platform. Custom CRM, project tracking, time logging, automated invoicing, and a client-facing portal. All in one app, built on their existing infrastructure, designed around their actual workflows instead of forcing them into someone else’s template.
The build cost $185K. Their first-year SaaS savings were $312K. That’s a net positive of $127K in year one. Every year after that, the savings get bigger because there are no per-seat subscription fees scaling with headcount.
They own the code. They own the data. No vendor can sunset their tier, jack up pricing, or hold their data hostage behind a $500 export fee.
Why this works now and didn’t two years ago
Two things changed.
First, AI cut the cost and timeline of custom software development. What used to take a team of six developers eight months can now be scoped, designed, and built by a smaller team in a fraction of the time. We use LLMs across every stage of our delivery process, from drafting technical specs to generating test suites to writing documentation. The productivity gain is real, and we pass it directly to clients through lower project costs.
Second, SaaS pricing went in the opposite direction. Per-seat costs have climbed steadily. Enterprise tiers keep getting more expensive. The “land and expand” model means most companies are paying for features they’ll never use just to keep the three features they actually need.
The crossover point, where custom-built is cheaper than rented, has moved. For a lot of mid-market companies, it’s already here.
What Service as Software actually includes
We’re not just writing code and handing over a repo. The model has three parts.
Discovery and audit. We map your current SaaS stack, identify what’s redundant, what’s underused, and what’s actually earning its keep. Not everything should be replaced. Some tools are best-in-class and worth the subscription. We’re honest about that. The output is a prioritized roadmap with real cost projections.
Custom build. We design and build the replacement tools, integrated into a single platform or a small set of purpose-built applications. Everything is built on modern, maintainable code. No black boxes, no proprietary lock-in from us either. You get the source code, the infrastructure access, and full documentation.
Ongoing maintenance. Software needs care. We offer a monthly retainer that covers monitoring, security patches, dependency updates, minor feature requests, and AI model updates as the technology changes. Think of it as a fraction of what you were paying in SaaS fees, but for software that’s actually yours.
The fear we hear most often
“If we automate with AI, does that mean layoffs?”
No. And we actively position every project around this.
The professional services firm we mentioned didn’t cut a single role. Their operations team, the people who used to spend hours on manual data entry, CSV wrangling, and cross-referencing three dashboards, now spend that time on exception handling, client communication, and quality assurance. The same team, doing higher-value work, handling more volume.
AI cost savings without layoffs isn’t a tagline. It’s how the math actually works when you automate the tedious parts and let your people focus on judgment, relationships, and problem-solving.
Is this right for your company?
Honestly, not always. If you’re a 10-person startup still figuring out your workflows, SaaS is probably the right call. You need flexibility more than ownership. If your team runs on a single tool that does exactly what you need, don’t fix what isn’t broken.
But if you’re a 50 to 200 person company stacking tools on top of tools, spending six figures a year on subscriptions, and feeling the friction of systems that don’t quite fit, the math is worth running.
We’ll do the audit for free. If the numbers don’t make sense, we’ll tell you. If they do, we’ll show you exactly what the build looks like.
