April 2, 2026
"We're not a tech company. We don't build software. That's why we buy it."
For decades, that was the right answer. If your business didn't have engineers on staff, building custom software was out of reach. The cost was prohibitive, typically $500,000 or more per year when you factored in development, maintenance, and the technical talent to manage it. So you bought SaaS. Whatever was available in your industry, you licensed it and moved on.
That math is changing. Not because non-technical companies are suddenly becoming software shops, but because the cost of building and maintaining custom software has collapsed to the point where it's no longer reserved for companies with engineering teams.
This article extends our Build vs. Buy AI framework for companies that have historically never had a software function. If you've always been a buyer, here's when it might start making sense to build.
The logic was simple and correct. You run a services business, a retail operation, a healthcare practice, a logistics company. You don't know how to build software, and you shouldn't need to. The SaaS industry exists to solve that problem. Vendors build horizontal tools meant to serve thousands of companies across dozens of industries, and you pick the ones that fit closest to your needs.
The tradeoff was always compromise. Horizontal software serves many industries, which means it's designed for the average use case, not yours. You end up settling for features that mostly work, or hacking workarounds to get the tool to match how your business actually operates. That compromise was acceptable because the alternative, building custom, was simply too expensive.
Two things have shifted the math.
The cost of custom software has dropped dramatically. What used to cost $500,000 or more per year is now landing in the $100,000 range or below for the first year, including the cost of someone to manage it. That's still a meaningful investment. But it's a fundamentally different conversation than half a million dollars. And the trajectory is clear: as AI-driven development tools continue to improve, that number is heading toward $50,000 per year or less on an ongoing basis.
AI-powered tools can build functional software without a traditional dev team. Agentic coding tools and no-code platforms have reached a level of maturity where non-technical teams can stand up working internal applications by describing what they want in plain language. MIT Technology Review named "generative coding" one of its 10 Breakthrough Technologies for 2026. The ratio of citizen developers to professional software engineers is approaching 4:1 according to industry analysts, and 81% of companies now list low-code/no-code as a critical strategic asset.
This doesn't mean you can build enterprise software with a prompt and a prayer. But for the kinds of internal tools that many businesses license as SaaS today, CRM, workflow management, dashboards, scheduling, reporting, the gap between "off the shelf" and "custom built" is narrower than it's ever been.
The most honest thing about the build vs. buy decision for non-technical companies is that ownership shows up on both sides of the ledger.
Ownership as a pro: When you own the software, you own the roadmap. You're not waiting for a vendor to prioritize your feature request alongside thousands of other customers. You're not locked into a pricing model that increases 15% at renewal. You're not hacking a horizontal tool to match your specific workflow. You get software that does exactly what your business needs, and you can change it whenever you want.
Custom workflows create real velocity. When the software matches how your team actually works instead of forcing them into a vendor's assumptions, things move faster. That speed compounds over time.
Ownership as a con: Someone in your organization has to be responsible for it. Even as AI agents become capable of building and maintaining software with minimal human intervention, a human still needs to oversee the system, make decisions about priorities, and be accountable when something breaks.
This is the cost you can't eliminate. You need a person, not necessarily a full-time software engineer, but someone with enough technical literacy to manage AI agents and make judgment calls. That's a real allocation of time and attention.
Here's the nuance the transcript speaker nailed: most companies already have someone who "owns" their SaaS tools internally. Someone manages the Salesforce configuration. Someone handles the HubSpot workflows. Someone is the point person for the project management tool. When you move from buying to building, that person's role shifts, but it doesn't necessarily create new headcount. The time gets redeployed, not duplicated. Which means the actual cost delta between buying and building may be smaller than it looks on paper.
First-year setup cost: Around $100,000, including initial development and the time allocation of someone to own the project. This can come in lower for simpler tools, higher for complex workflows with multiple integrations.
Ongoing annual cost: Trending toward $50,000 or less. This covers maintenance, updates, and the incremental time of the person responsible for it. As AI agents improve at self-maintaining codebases, this number continues to drop.
The comparison that matters: Take the annual cost of the SaaS tools you'd replace, add the internal time your team already spends managing those tools, and compare that to the cost of owning custom software that does exactly what you need. For many companies, the math now tips toward building, particularly for tools where the SaaS license is substantial and the workflow fit is poor.
The SaaS tool doesn't match your workflow. You're spending significant time working around the tool's limitations or paying for customization that doesn't quite get you there. The gap between what the tool does and what you need is costing you in productivity, workarounds, and frustration.
The annual SaaS cost is significant. If you're spending $50,000 or more per year on a tool that only gets you 70% of the way, building a custom alternative that gets you 100% of the way starts to look like a sound investment, especially when the total cost of ownership is in the same range.
You have someone who can own it. This doesn't mean a developer. It means someone with operational knowledge of your business and enough comfort with technology to manage AI-powered development tools and oversee the system. In 2026, that person might use a no-code platform like Lovable or Bubble, or they might work with a team like Fraction to scope and build it.
The tool is relatively straightforward. CRM, internal dashboards, scheduling, workflow automation, reporting. These are categories where AI-built custom software is already proven. If the software you need is highly specialized (medical devices, financial compliance engines, complex supply chain optimization), the buy or partner route likely still makes more sense.
The SaaS tool works well and costs less than a few hundred dollars per month. The ROI on building a replacement isn't there. Use the tool. Move on.
The vendor is deeply specialized in your industry. A vertical SaaS product built specifically for your sector by a team that understands your regulatory environment, your workflows, and your data requirements is hard to replicate. That specialization is what you're paying for.
You don't have anyone who can own a custom tool. If there's no one in your organization who can manage the software once it's built, you'll end up with an abandoned internal tool that nobody maintains. That's worse than an imperfect SaaS subscription.
A few years ago, the build option was off the table for non-technical companies. The cost was too high, the expertise was too specialized, and the risk was too large. Today, the threshold has dropped to around $100,000 for the first year, with ongoing costs heading toward $50,000 or less. Tomorrow, it will be lower.
That doesn't mean every company should start building. It means the question is now worth asking for companies that never would have considered it before. For a much larger array of businesses, building custom software is now a real option, not a fantasy.
The companies that benefit most won't be the ones that rush to replace every SaaS tool in their stack. They'll be the ones that identify the one or two tools where the fit is worst and the cost is highest, and start there.
At Fraction, we build custom software for companies across the technical spectrum. Our project planner will scope what a custom build looks like for your specific use case at $149 per story point, with a breakdown before you commit. If the buy option wins on the numbers, we'll tell you. If the build option wins, you'll have a clear estimate to act on.
Related reading: Build vs. Buy AI: When to Build Custom and When to Use Off-the-Shelf, Build vs. Buy AI for Tech Companies: When the Math Changes, AI Strategy for Non-Technical Founders
Sources
MIT Technology Review, "Generative Coding: 10 Breakthrough Technologies 2026," January 12, 2026. AI coding tools named a breakthrough technology; AI writes up to 30% of code at Microsoft and over 25% at Google.
EditorialGE, "No-Code for Enterprise in 2026," January 2026. Reports citizen developer to professional developer ratio approaching 4:1; 81% of companies list low-code/no-code as a critical strategic asset.
Xtract.io, "How Low-Code Development Platforms are Powering AI in 2026," February 2026. Covers the shift to intent-based software creation and the mainstreaming of "vibe coding" in enterprise contexts.
NeuralStackly, "What Is Vibe Coding 2026," February 2026. Synthesizes MIT Tech Review, ZDNET, and NYT reporting on AI-built apps by non-technical users.
Deloitte, "SaaS meets AI agents," November 2025. Predicts up to half of organizations will allocate more than 50% of digital transformation budgets toward AI automation in 2026.
