One of the most consequential decisions in any AI initiative is whether to build a custom solution or buy an existing one. Get it wrong, and you’ll either spend six months building something that already exists — or lock yourself into a vendor product that can’t do what you actually need.
Having built AI products from scratch (Marvel PTE, now serving 85,000+ users) and deployed off-the-shelf solutions for clients, I’ve developed a framework for making this decision that I wish I’d had earlier in my career.
When to Buy
Buy when the problem is well-defined and common. If thousands of other companies have the same challenge, someone has probably already built a good solution for it.
Examples where buying makes sense:
- Email marketing automation — tools like Mailchimp, HubSpot, and Klaviyo have AI features that work well out of the box
- Customer support chatbots — platforms like Intercom and Zendesk offer solid AI-powered support
- Basic data analytics — tools like Tableau and Power BI handle standard reporting well
- CRM with AI features — Salesforce Einstein, HubSpot AI, etc.
The buy signal: If you can describe your needs in terms the vendor already uses on their marketing page, buying is probably the right call.
When to Build
Build when your competitive advantage depends on it. If the AI solution IS the product, or if it needs to integrate deeply with proprietary data and processes that no vendor can access, building custom is the way to go.
Examples where building makes sense:
- Industry-specific scoring or classification — like our Marvel PTE scoring engine, which needed to evaluate English language proficiency with accuracy comparable to human examiners
- Custom workflow automation — when your processes are genuinely unique and can’t be mapped to a vendor’s workflow template
- Proprietary data models — when you have data that gives you a competitive edge and needs AI interpretation that doesn’t exist elsewhere
- Deep system integration — when the AI needs to operate inside your existing stack in ways that APIs and webhooks can’t handle
The build signal: If you find yourself asking a vendor “can it do X?” more than three times during a demo, and the answer keeps being “not yet, but it’s on our roadmap,” you probably need to build.
The Hybrid Approach
Most mature AI strategies end up as hybrids. You buy commodity capabilities — the things that everyone needs and that are well-served by existing tools — and build the differentiated capabilities that create your competitive edge.
At SIAGB, this is how we approach most client engagements:
- Audit existing tools — often clients are paying for AI features they’re not using in tools they already own
- Identify gaps — where do off-the-shelf tools fall short of what the business needs?
- Build only the gaps — custom solutions for the 20% of capability that drives 80% of the value
- Integrate everything — the custom and off-the-shelf components need to work together seamlessly
Cost Considerations
The total cost of ownership calculation is often more complex than it appears:
Buying:
- Lower upfront cost, higher long-term subscription cost
- Vendor lock-in risk
- Limited customisation
- Someone else handles maintenance and updates
Building:
- Higher upfront cost, lower marginal cost at scale
- Full control and ownership
- Exactly what you need (if scoped well)
- You’re responsible for maintenance, hosting, and updates
The crossover point is typically 18-24 months. If you’ll be using the solution for less than two years, buy. If it’s a core capability you’ll rely on for five years or more, building often makes more financial sense.
The Bottom Line
Don’t let ego drive the decision. “We build everything ourselves” is as dangerous as “we buy everything off the shelf.” The right answer depends on whether AI is your core competency or a supporting capability — and whether the specific problem you’re solving is common enough to have existing solutions.
Start by defining what you need, not by evaluating vendors or estimating development timelines. The requirements should drive the build-vs-buy decision, not the other way around.