How Much Software Development Actually Costs: A Startup Budgeting Breakdown
Real price bands for MVPs, SaaS platforms, AI integrations, and enterprise systems — and the handful of decisions that move the number more than anything else.
How much does it cost to build a SaaS product? Every calculator gives you a number in under thirty seconds, and none of them ask the two questions that actually decide it: how complex is the real feature set, and how fast do you need it. Here's what a project actually costs, broken down by the variables that move the number — not a generic multiplier.
Why most online cost calculators are useless
Type "SaaS MVP cost" into Google and you'll get a dozen calculators that ask for your industry and spit out a number. The problem isn't that the number is wrong — it's that it's not attached to anything. A to-do app and a multi-tenant billing platform can both get called "SaaS," and they cost four times apart. The variables that actually matter aren't industry or headcount — they're scope, integration surface, and timeline.
What actually moves the number
Four things, in order of impact. Complexity: a handful of CRUD screens vs. real-time, multi-tenant, custom infrastructure. Integrations: every third-party system — auth, payments, CRM, a legacy API — adds real engineering time, not a checkbox. Data model: multi-tenancy and background jobs cost more than they look like on a whiteboard. Timeline compression: a rushed deadline needs more people working in parallel, and more people means coordination overhead, not linear speed-up.
Ballpark ranges, by project type
These are ballparks for a senior, small-team engagement — not an industry average, and not what you'd pay an agency billing by headcount instead of outcome.
Web app / MVP: $30K–$60K, 6–10 weeks
Mobile app: $40K–$80K, 8–14 weeks
SaaS product / platform: $60K–$120K, 10–18 weeks
AI agent / LLM integration: $50K–$100K, 8–16 weeks
Enterprise system: $100K–$220K+, 14–28 weeks
The MVP-first argument, in dollars
The temptation is always to build the full vision upfront. It's almost always the wrong call financially. A startup that spends $45K on a focused MVP and $80K refining it based on real usage nearly always ends up cheaper — and with a better product — than one that spends $150K upfront guessing at a full feature set nobody's validated yet.
Where budgets quietly blow up
Not from bad engineering — from scope that was never actually written down:
An undefined "a few integrations"
Compliance requirements (SOC2, HIPAA) discovered mid-build
Design churn treated as free because it's "just Figma"
Data migration with no documented source schema
Timeline compression requested late instead of planned for at the start
What we've actually run into
The projects that blow past budget almost never do it because of bad engineering — they do it because scope was agreed on a slide, not a spec. The fix isn't a bigger contingency line item, it's writing the actual feature list down before anyone quotes a number.