One of the most useful things we do for clients isn't building something. It's telling them when they don't need us.
The AI tools market is genuinely good now. There are off-the-shelf products that handle customer support, knowledge management, sales enablement, and dozens of other use cases. For some teams, buying one of these tools is the right answer.
Here's how we think about when to buy and when to build.
When to buy
Buy an off-the-shelf tool when your use case is standard.
If you need a customer support chatbot that handles FAQs, routes tickets, and integrates with your helpdesk, there are mature products that do this well. These tools are fast to deploy, require minimal configuration, and come with support. If the workflow you're trying to improve matches what the tool was built for, buying is almost always more cost-effective than building.
When to build
Build a custom assistant when your workflow has characteristics that off-the-shelf tools can't accommodate.
Proprietary knowledge — if the assistant needs to work with information specific to your business, a generic tool won't have it. Training a custom assistant on your actual data produces dramatically better results.
Non-standard workflow — if the task doesn't map cleanly to a category a product was designed for, you'll spend more time bending the tool to fit than it would have taken to build something that fits natively.
Output quality matters a lot — in customer-facing contexts, the calibration of a custom assistant trained on your specific data typically outperforms a generic tool.
The honest middle ground
In many cases, the right answer is to start with a product and build custom when you hit its limits. This lets you validate the use case cheaply before investing in a build.
We tell clients this directly. If a product exists that would solve 80% of the problem at 20% of the cost, we say so. We'd rather be trusted advisors than vendors who build things that didn't need building.
If you're not sure which side of the line you're on, that's exactly the kind of question we answer in a discovery call.