If you're a developer who's been asked "how much will this cost?" by a non-technical founder - or if you're a founder trying to make sense of wildly different quotes - this is the breakdown you actually need.
Why the range is so wide

App development cost isn't a fixed menu. It's the output of compounding decisions: team seniority, architecture complexity, platform choice, third-party integrations, and design depth. Each variable multiplies against the others.

Higher rates don't always mean better code. They mean more defined processes, faster communication cycles, and engineers who've seen enough production incidents to know what not to do.

**Platform cost comparison
**React Native / Flutter (cross-platform): baseline Native iOS + Android (separate codebases): 40–60% higher
For most Indian consumer apps targeting a broad Android-first user base: start cross-platform. Migrate to native when your performance requirements genuinely demand it.
Build cost ranges

MVP (1–3 features, locked scope): ₹8L–₹25L Mid-complexity (auth, integrations, dashboards): ₹25L–₹80L Full platform (multi-role, real-time, complex logic): ₹1Cr–₹4Cr+
Integration complexity - the hidden cost driver
Every third-party integration your app touches adds engineering overhead that rarely shows up in initial quotes:

Razorpay: webhook handling, refund flows, subscription logic
Shiprocket / Delhivery: order sync, tracking callbacks, failure states
GST APIs: compliance edge cases that multiply rapidly
Firebase / AWS Amplify: real-time sync, offline handling, cost at scale
Spec every integration before the build starts. Discovering them mid-sprint is the single most common cause of budget overrun.

**AI/ML cost layers
**Level 1: API integration (OpenAI, Anthropic, Gemini)
Cost: ₹4L–₹15L
Complexity: Medium - prompt engineering, rate limiting, fallback handling

Level 2: Custom ML feature (recommendation, classification, parsing)
Cost: ₹12L–₹35L
Complexity: High - data pipeline, model selection, evaluation loops

Level 3: AI-core product (fine-tuning, custom training, inference infra)
Cost: ₹80L+
Complexity: Specialist team required
Level 3 needs a proper AI development company with dedicated ML engineers - not a full-stack web team that's added "AI" to their homepage.
Post-launch operational costs
These are real and consistently underestimated:
AWS / GCP / Azure: bills arrive in USD
Razorpay, Cashfree: per-transaction fees that scale with usage

Play Store / App Store: 15–30% on in-app purchases
Maintenance dev: roughly 15–20% of build cost annually
On-call / monitoring: often forgotten until something breaks in production
For a ₹25L build: budget ₹10L–₹20L/year in running costs.
Evaluating a quote technically

Ask for: hourly rate + estimated hours per sprint, broken down by feature. A ₹25L quote at ₹5,000/hr implies 500 hours. That's a credible mid-complexity build. If they won't break it into hours, the number isn't based on a real estimate.

Also ask: what does discovery cost, who specifically is assigned, and what's the post-launch support SLA.