Custom software should never be the automatic answer. The first question is not which technology to use, but whether the problem truly requires a new tool.
A clear signal appears when a company’s process is too specific for available platforms. General tools may offer hundreds of features and still force teams to maintain parallel spreadsheets, repeat data or adapt their operation to someone else’s logic.
Control may also be a valid reason. Some companies need to decide where their data lives, how it integrates and who can access it. That need must be concrete: owning everything does not justify the cost of building and maintaining software by itself.
Artificial intelligence has made many tools faster and more accessible to build. But reducing coding time does not remove decisions about architecture, security, product, integration and maintenance.
The best recommendation before building is to test what already exists. If a tool works, there may be no reason to replace it. If it fails, that experience will define exactly what is missing.