That is exactly what these comparisons are for. Each one lays out the honest trade-offs on cost, speed, risk and ownership so you can see where you land. If you would rather not weigh it up alone, the free AI Readiness Audit maps your workflows and tells you which approach fits your situation, with no pitch attached.

You can, and for a handful of simple, low-stakes automations that is often the right call. The limits show up as you scale: brittle flows, no error handling, and a system only one person understands. We are happy to point you to what you can safely build yourself, and to take on the parts where a mistake is expensive.

Great, that usually makes projects faster, not redundant. A technical hire is brilliant at execution but rarely has the time or the cross-industry pattern library to design the whole system. Most firms get the best result when we set the architecture and hand your in-house person a system they can own and extend.

It happens often, and it is fixable. The usual failure is automating a process that was never properly mapped, so the tool amplifies a broken workflow. We can pick up a stalled DIY build, map what should have come first, and rebuild the parts that matter without you starting from scratch.

Both, chosen to fit the job rather than a preference. Where a no-code platform is reliable and cheaper to run we use it; where you need control, compliance or performance it cannot give, we build custom. Either way you own the result outright, with no lock-in to us.