The dominant factor is not the choice of framework — it remains uncertainty. Every open question in the requirements turns into a contingency in the estimate. A supplier that does not know the exceptions and edge cases has to assume the worst. Putting two weeks into requirements work frequently cuts the final cost much more than negotiating the rate.
Connections to other systems tend to be the second big multiplier. A screen that writes to your own database is easy to estimate; the same functionality talking to a legacy ERP is not. The cost sits in the other system: poor documentation, long certification processes, fields that mean something different on each side. Ask the estimator to list every external system, as this is the usual source of overruns.
Non-functional requirements quietly rewrite the budget. A tool used by twenty people has almost nothing in common with the same feature set handling public traffic. Compliance work, high availability, performance under load, data retention rules and edtech web development localisation all add real engineering time. Write them down at the start livewire or react you can expect them to arrive later as change requests.
The team you are quoted changes the arithmetic. A rate card says little on its own: a senior engineer at a higher rate can be less expensive in the end than two juniors who need heavy code review. Ask as well who else is billed: coordination, quality assurance, infrastructure work and UX design are real work, but these should be itemised.
The build price is not what you will actually spend. Budget for infrastructure, third-party licences, logging and alerting and a change budget annually. A reasonable rule of thumb says that ai software development company in active use consumes a noticeable fraction of its original build cost per year for updates, security patches and small improvements. Treating the launch as the finish line is the most frequent planning error.
