Every vendor has a timeline claim, and almost none of them are lying. They are quoting the fastest honest case for the smallest honest scope. A no-code platform can stand up a single simple product in a couple of weeks; a full enterprise core replacement can run a year or two. The number that matters is not the one in the brochure. It is the one that applies to your data, your integrations, and your decisions. Four variables set it.
1. The state of your data
Migrating in-force policies, open submissions, and historical records is usually the single largest driver of a timeline, and it is almost never quoted accurately up front, because no one has looked at your data yet. "Standard migration" is priced before inspection; the real scope arrives after. Clean, well-structured data in one system moves quickly. Data spread across an AMS, a rater, spreadsheets, and email (the normal condition of a growing MGA) takes longer to reconcile and validate, and validation is the part you cannot skip without betting a renewal on it.
2. How many integrations have to work
Each carrier feed, each rater connection, each accounting or document sync is its own piece of work with its own failure modes. A system that has to talk to three carriers and a rater on day one is a different timeline than one that stands alone. This is why the integration inventory belongs at the start of the project, not the middle: the count and complexity of the connections is a schedule input, and pretending otherwise is how "live in weeks" becomes "live, eventually."
3. How many decisions you still owe
Implementations stall on decisions more often than on code. Rates, forms, workflow rules, user permissions, report formats, every unresolved question is a pause. A vendor can only move as fast as it gets answers, and a founder-led team with a day job answers on its own schedule. This one is inside your control: the faster the sign-offs, the shorter the calendar. It is also why a fixed-scope phase beats an open-ended build, a phase names exactly which decisions are due and when.
Moving mundane, redundant work (intake, chasing, matching, assembly) to an AI Operational Workforce does not empty that decision queue, it separates it. The repeated work runs with feedback loops that correct it as it goes, while the decisions that touch rating or binding stay with your people, which is why those sign-offs, not the software, tend to set the calendar.
4. How much has to be right on the same day
The riskiest schedules are the ones with a single cut-over date where everything must work at once. That is the enterprise-implementation pattern the market fears, and it is fragile by construction: one slipped dependency moves the whole date. The alternative is not a faster miracle. It is a different shape.
Why phasing changes the question
A phased build does not promise a faster single date. It removes the single date. Each phase has a fixed scope, runs in parallel with your current process, and goes live only when it has proved itself, so no renewal depends on a cut-over that hasn't happened yet. The timeline stops being one long held breath and becomes a series of small, provable steps. That is the whole point of the phased method: not to win the timeline argument, but to make the timeline stop being the thing you gamble on.
Timelines also vary by what you build first. A broker rating portal that connects to your existing rater is a different schedule than a carrier-reporting hub that has to reconcile every program's data, which is exactly why the sequence matters, and why our guide to choosing MGA software puts shape-on-paper before any timeline promise.
The most useful thing you can do before shortlisting anyone is to ask for the timeline drivers in writing (data state, integration count, decision list, cut-over shape) and treat a vendor's willingness to name them as information about how the project will actually run. If you would rather see your own drivers mapped against your real systems, that is what a free mapping session is for.