MVP Development Timeline: What Realistic Looks Like (By Project Type)

TL;DR: Every MVP Timeline Depends on 3 Variables

The 3 variables that determine your timeline:

1. Feature count: 3-5 features = fast. 10+ features = you're not building an MVP.
2. Integration complexity: Auth + payments = standard. Custom AI + 5 third-party APIs = add 2-3 weeks.
3. Development approach: Traditional = X weeks. AI-accelerated = X/2 weeks.

Here are the benchmarks we use for scoping calls.

Web App MVP: 2–4 Weeks (SaaS, Dashboard, Internal Tool)

The most common MVP we build. Typical scope: user authentication, 3-5 core features, database, admin panel, deployment.

Examples delivered: • B2B SaaS dashboard with Stripe billing: 3 weeks, $8,000 • Internal ops tool with approval workflows: 2 weeks, $5,000 • Customer portal with AI-powered search: 4 weeks, $12,000

Tech stack: Next.js + PostgreSQL + Vercel. This combination lets us move fastest because it handles server rendering, API routes, and deployment in one framework.

Timeline breakdown: Week 1 — architecture + auth + database. Week 2 — core features. Week 3 — polish + testing + deploy. Week 4 (if needed) — integrations + edge cases.

Mobile App MVP: 3–6 Weeks (iOS + Android via React Native)

We build mobile MVPs with React Native — one codebase, two platforms, real app store deployment.

Typical scope: onboarding flow, 3-5 screens, push notifications, API integration, app store submission.

Examples delivered: • Fitness tracking app with AI coaching: 5 weeks, $15,000 • Service marketplace mobile app: 6 weeks, $18,000 • Event management app with QR check-in: 3 weeks, $9,000

The extra 1-2 weeks vs web apps comes from: app store review process (1-3 days per submission), mobile-specific UX patterns, and device testing across screen sizes.

Important: if your product works as a responsive web app, skip mobile for v1. Mobile adds 50% to timeline and cost. Launch web-first, validate, then go mobile.

AI-Powered App: 4–8 Weeks (LLM, RAG, AI Agents)

AI features add complexity because they require: model selection, prompt engineering, RAG pipeline setup (if using your data), testing for hallucinations, and ongoing optimization.

Timeline by AI complexity: • Simple LLM integration (chatbot, summarization): +1-2 weeks to base timeline • RAG system (search your documents): +2-3 weeks • AI agent (multi-step reasoning, tool use): +3-4 weeks • Fine-tuned model: +4-6 weeks (data preparation is the bottleneck)

Examples delivered: • Legal document intelligence (RAG): 6 weeks, $25,000 • AI sales qualification agent: 3 weeks, $8,000 • LLM-powered customer support: 5 weeks, $18,000

Pro tip: don't build custom AI from scratch for your MVP. Use pre-built models (GPT-4, Claude) with good prompt engineering first. Fine-tune later if the numbers justify it.

Marketplace MVP: 4–8 Weeks (Two-Sided Platforms)

Marketplaces are the hardest MVP to get right because you're building for two user types simultaneously.

Minimum viable marketplace needs: supply-side listings, demand-side search/discovery, messaging or matching, payment/escrow, and reviews/ratings.

Timeline reality check: • Week 1-2: Core platform (auth, listings, search) • Week 3-4: Transaction flow (payments, booking, messaging) • Week 5-6: Trust features (reviews, verification, dispute resolution) • Week 7-8: Polish, testing, launch

Our advice: launch one side first. If you're building a freelancer marketplace, start with supply (freelancer profiles) and manually match the first 20 clients. Don't automate matching until you understand what 'good match' means from real data.

What Makes Timelines Slip (And How to Prevent It)

The 5 timeline killers we see every quarter:

1. Scope creep: 'Can we also add...' after week 2. Fix: lock scope in Day 1. Change orders require written approval.
2. Decision delay: Founder takes 5 days to choose between two designs. Fix: 24-hour decision windows in the project charter.
3. Third-party API surprises: The payment provider takes 2 weeks to approve your account. Fix: start integrations in parallel with core development.
4. Perfectionism: 'The button color isn't right' blocks deployment. Fix: ship to staging weekly, only block on functional issues.
5. No product owner: Nobody can answer 'which feature is more important?' Fix: designate one person with final say before day 1.

How AI-Accelerated Development Cuts These in Half

Every timeline above assumes AI-accelerated development. Here's what that means in practice:

• UI components: AI generates 80% of UI code from design references. Engineers refine the remaining 20%. • Boilerplate: Auth, database schemas, API routes — AI scaffolds these in hours, not days. • Testing: AI generates test cases from feature specs. Engineers review and extend. • Documentation: AI drafts technical docs from codebase. Engineers verify accuracy.

Net effect: a 12-week project in 2024 is a 5-week project in 2026. Same quality, same senior engineers — just faster tools.

This is not 'vibe coding.' Every AI output is reviewed by a senior engineer before it ships.

Get a Timeline Estimate for Your Specific Project

Every project is different. The timelines above are benchmarks, not guarantees.

Book a free 30-minute scoping call and we'll give you: • A specific timeline for your project type and feature set • A fixed-scope price (no hourly billing) • Honest assessment of what to include in v1 vs v2

We'll also tell you if you're not ready yet — some founders benefit more from 2 more weeks of user research than from starting development.