What Can You Really Build in 1-2 Weeks?

Bottom line: More than you think. We've delivered 50+ MVPs using our sprint process, from mobile CRMs to AI-powered tools to marketplace platforms. Here are 10 real examples with costs, timelines, tech stacks, and lessons learnt.

How to Use This Guide

Each product example includes:

• What it does: Core functionality
• Who it's for: Target users
• Build complexity: 1 week, 2 weeks, or 4 weeks
• Cost: Actual development cost
• Tech stack: What we used to build it
• What made it work: Key success factors
• Common mistakes: What to avoid

Find the example closest to your idea, see what's realistic, and understand what it takes.

1. Mobile CRM for Tradespeople (SalesLite)

What It Does

Mobile-first CRM designed for tradespeople who work on-site. Core features:

• Record voice notes that auto-convert to structured customer data
• AI transcription extracts names, addresses, job details
• Automated quote generation with PDF export
• Pipeline management (leads → quotes → jobs → complete)
• Customer database with history
• Push notifications for follow-ups

Who It's For

UK tradespeople: plumbers, electricians, builders, landscapers. Anyone who's always on-site and hates desktop software.

Build Complexity

2 weeks (Week 1: Core CRM, Week 2: AI features)

Week 1 delivered:

• Customer database
• Pipeline management
• Basic quote creation
• Mobile app (iOS/Android via React Native)

Week 2 added:

• AI voice transcription (OpenAI Whisper)
• Automated data extraction
• PDF quote generation
• Email integration

Cost

£25,000 (2-week sprint)

Tech Stack

Frontend: React Native (Expo) for iOS/AndroidBackend: Node.js + ExpressDatabase: PostgreSQL via SupabaseAI: OpenAI Whisper API for transcriptionFile Storage: Supabase Storage for audio filesPDF Generation: PDFKitHosting: Railway for backend, Supabase for database

What Made It Work

1. Clear target user: Not "small business owners" but specifically "tradespeople who work on-site"

2. Solved real pain: 25 user interviews revealed they use WhatsApp and paper notes because desktop CRMs are too complex

3. Mobile-first: Built for how they actually work (on phones, on-site, hands dirty)

4. Voice input: Game-changer for users who can't type whilst working

5. Fast validation: Working app in 2 weeks, tested with 50 tradespeople by Week 3

Results

• 100 beta users in first month
• 30% conversion to paid (£25/month)
• Average 4.8 stars in reviews
• Users say: "Finally something I'll actually use"

Common Mistakes to Avoid

Don't: Build desktop version first "just in case"
Do: Commit to mobile-first if that's where users are

Don't: Add every CRM feature (contact management, email campaigns, reporting)
Do: Focus on the unique workflow (voice → structured data → quotes)

Don't: Build custom voice transcription
Do: Use OpenAI Whisper API (saves 3-4 weeks)

Book a free discovery call to discuss your mobile app idea.

2. AI-Powered Document Analyser

What It Does

Upload PDFs (contracts, reports, research papers) and get instant AI-powered analysis:

• Automatic summarisation
• Key point extraction
• Question answering ("What are the payment terms?")
• Risk identification in contracts
• Citation extraction for research papers

Who It's For

Consultants, lawyers, researchers, anyone who reads lots of documents professionally.

Build Complexity

1 week (basic AI analysis)
2 weeks (with document upload, user accounts, and history)

Week 1 delivered:

• PDF upload
• AI analysis using Claude API
• Summary generation
• Key points extraction
• Simple web interface

Cost

£12,500 (1-week sprint)

Tech Stack

Frontend: Next.js with ReactBackend: Next.js API routesAI: Anthropic Claude APIFile Processing: PDF.js for text extractionDatabase: PostgreSQL via Supabase (for user history)Hosting: Vercel

What Made It Work

1. Single use case: Focused on contract analysis initially, not "analyse any document"

2. Used existing AI: Anthropic Claude API instead of custom ML model (saved 8+ weeks)

3. Simple workflow: Upload → Wait 10 seconds → Get results

4. Immediate value: Users see benefit in first 30 seconds

Results

• Launched to 200 beta users
• 78% completed first analysis
• 52% uploaded second document within 24 hours
• Clear willingness to pay (£49/month for unlimited)

Tech Insights

Why Claude API over custom model:

• Development time: 1 week vs 8+ weeks
• Quality: Claude's analysis is excellent out-of-box
• Cost: £0.015 per analysis vs £50K+ to train custom model
• Maintenance: Anthropic handles updates

API costs: £2-5 per 100 analyses (very manageable)

Common Mistakes to Avoid

Don't: Build document OCR from scratch
Do: Use PDF.js for text extraction, Anthropic Claude for analysis

Don't: Try to handle every document type
Do: Start with PDFs, add others later if validated

Don't: Build complex dashboard before validation
Do: Single page: upload → results

3. Booking Platform for Local Services

What It Does

Two-sided marketplace for local services (starting with dog groomers):

• Service providers create profiles and set availability
• Customers browse, compare, and book appointments
• Integrated payment via Stripe
• Automated email confirmations
• Calendar sync for providers

Who It's For

Service providers who take bookings (initially dog groomers, expandable to hairdressers, personal trainers, tutors, etc.)

Build Complexity

4 weeks

Week 1-2:

• Provider signup and profiles
• Service listing creation
• Customer booking flow
• Calendar/availability system

Week 3:

• Stripe payment integration
• Email confirmations
• Booking management

Week 4:

• Reviews and ratings
• Search and filtering
• Polish and testing

Cost

£50,000 (4-week sprint)

Tech Stack

Frontend: Next.js with ReactBackend: Next.js API routes + SupabaseDatabase: PostgreSQL via SupabasePayments: Stripe Connect (marketplace payments)Email: Resend for transactional emailsHosting: Vercel

What Made It Work

1. Niche first: Dog groomers only, not "all local services"

2. Provider-friendly: Made it easy for groomers to set up and manage

3. Payment built-in: Customers pay through platform, providers get payouts

4. Mobile-responsive: Works on phones (where most bookings happen)

Results

• 45 groomers signed up in first month
• 380 bookings in first 6 weeks
• £12,500 GMV (Gross Merchandise Value)
• 3% platform fee = £375 revenue
• Clear path to profitability

Marketplace-Specific Challenges

Chicken-and-egg problem:

• Need providers to attract customers
• Need customers to attract providers

Solution:

• Launched in single city (Manchester)
• Manually onboarded first 10 groomers
• Gave them free listings for 3 months
• Drove customers via local Facebook groups
• Once booking volume proved valuable, charged providers

Payment complexity:

• Used Stripe Connect for marketplace payments
• Providers get 97% (platform takes 3%)
• Automated payouts weekly

Common Mistakes to Avoid

Don't: Launch in multiple cities at once
Do: Prove it works in one city first

Don't: Build custom payment processing
Do: Use Stripe Connect (handles escrow, payouts, disputes)

Don't: Try to be Uber/Airbnb immediately
Do: Start with simple booking flow, add features based on usage

Book a free discovery call to discuss your marketplace idea.

4. Habit Tracking App with AI Insights

What It Does

Mobile app for building better habits:

• Daily habit tracking (mark complete/incomplete)
• Streak tracking and motivation
• AI-powered insights based on completion patterns
• Personalised suggestions for improvement
• Social accountability (optional sharing with friends)

Who It's For

People trying to build consistent habits: exercise, reading, meditation, healthy eating, learning.

Build Complexity

2 weeks

Week 1:

• Habit creation and management
• Daily check-in interface
• Streak tracking
• Basic analytics
• Mobile app (iOS/Android)

Week 2:

• AI insights (OpenAI GPT-4)
• Pattern recognition
• Personalised suggestions
• Push notifications for reminders

Cost

£25,000 (2-week sprint)

Tech Stack

Frontend: React Native (Expo)Backend: Supabase (auth, database, real-time)AI: OpenAI GPT-4 for insightsNotifications: Expo push notificationsStorage: Supabase for user dataHosting: Supabase backend, Expo for app distribution

What Made It Work

1. Simple core loop: Check in daily → See streak → Feel motivated

2. AI adds value: Weekly insights like "You're more likely to exercise on weekdays" or "Your reading streak breaks on Sundays - try morning instead?"

3. Friction-free: 3 taps to check in a habit (no complex logging)

4. Visual progress: Seeing 47-day streak is motivating

Results

• 500 downloads in first month (organic)
• 68% daily active users (very high for habit apps)
• Average 3.2 habits tracked per user
• 12% upgraded to premium (£4.99/month)
• Strong retention (45% still active after 30 days)

Mobile App Insights

Why React Native:

• One codebase for iOS and Android
• Native performance
• 90% code reuse

Push notifications are critical:

• 2x daily active users with reminders
• Users set preferred reminder time
• Don't spam (max 3 per day)

Common Mistakes to Avoid

Don't: Add social features before core habit tracking works
Do: Nail the individual experience first

Don't: Require complex onboarding
Do: Let users add first habit in under 30 seconds

Don't: Track too many metrics per habit
Do: Simple complete/incomplete is enough

5. Team Knowledge Base with AI Search

What It Does

Internal knowledge base for teams with AI-powered search:

• Document upload (PDFs, Docs, text files)
• Automatic categorisation and tagging
• AI-powered semantic search ("How do we handle refunds?" returns relevant policies)
• Chat interface for asking questions
• Team collaboration (comments, updates)

Who It's For

Small teams (5-50 people) who need to organise and find company knowledge quickly.

Build Complexity

3 weeks

Week 1:

• Document upload and storage
• Basic categorisation
• Search functionality
• Team authentication

Week 2:

• AI embeddings for semantic search (via OpenAI)
• Vector database (Supabase pgvector)
• Retrieval-augmented generation (RAG)
• Chat interface

Week 3:

• Team permissions
• Collaboration features
• Polish and testing

Cost

£37,500 (3-week sprint)

Tech Stack

Frontend: Next.js with ReactBackend: Next.js API routesDatabase: PostgreSQL via SupabaseVector DB: Supabase pgvector extensionAI: OpenAI for embeddings and GPT-4 for answersFile Storage: Supabase StorageAuth: Supabase Auth with team/org supportHosting: Vercel

What Made It Work

1. Better than Google Drive search: Understands intent, not just keywords

2. Answers questions directly: Instead of returning 50 documents, gives you the answer with source citations

3. Team context: Knows your company terminology and processes

4. Easy to populate: Bulk upload existing Google Drive/Dropbox files

Results

• 12 teams using it (60-200 employees each)
• Average 40% reduction in "How do I...?" Slack questions
• 85% of searches find relevant answer
• £199/month per team (5-20 users)
• Strong word-of-mouth growth

AI Implementation Details

RAG (Retrieval-Augmented Generation) approach:

1. User asks question
2. Convert question to embedding
3. Search vector database for relevant document chunks
4. Send chunks + question to GPT-4
5. GPT-4 answers based on company docs, not general knowledge

Why RAG instead of fine-tuning:

• Cheaper (no training costs)
• Faster (works immediately)
• Updates easily (just add new docs)
• More accurate (grounds answers in source material)

Embedding costs: ~£0.10 per 1,000 pages (one-time)
Search costs: ~£0.01 per query

Common Mistakes to Avoid

Don't: Try to build custom embeddings model
Do: Use OpenAI embeddings (excellent quality, cheap)

Don't: Send entire document library to GPT-4 each query
Do: Use RAG to retrieve only relevant chunks

Don't: Skip source citations
Do: Always show which document the answer came from

Book a free discovery call to discuss your AI tool idea.

6. Freelancer Invoice and Payment Platform

What It Does

Simple invoicing for freelancers:

• Create professional invoices in 60 seconds
• Send via email or shareable link
• Clients pay online via Stripe
• Automatic payment reminders
• Expense tracking
• Basic tax calculations (UK-specific)

Who It's For

UK freelancers who hate complex accounting software. Just want to get paid easily.

Build Complexity

2 weeks

Week 1:

• Invoice creation
• Client management
• PDF generation
• Email sending

Week 2:

• Stripe payment integration
• Payment tracking
• Automated reminders
• Basic expense tracking

Cost

£25,000 (2-week sprint)

Tech Stack

Frontend: Next.js with ReactBackend: Next.js API routesDatabase: PostgreSQL via SupabasePayments: Stripe Checkout + ConnectPDF Generation: React-PDFEmail: ResendHosting: Vercel

What Made It Work

1. Stupid simple: Create invoice → Send → Get paid. No complex features.

2. Beautiful invoices: PDF output looks professional (matters to freelancers)

3. Payment friction removed: Client clicks link, pays with card. No bank transfers.

4. Fair pricing: Free for first 3 invoices, then £12/month unlimited

Results

• 2,400 freelancers signed up in first 3 months
• 45% active monthly (create at least 1 invoice)
• Average £380 invoice value
• 18% convert to paid plan
• £5,184 MRR after 3 months

Payment Flow Insights

Why Stripe:

• Handles card processing, security, compliance
• Works globally
• 2.9% + 30p per transaction (industry standard)
• Automatic payouts to freelancer

Platform revenue model:

• Don't take cut of payments
• Charge monthly subscription instead
• Keeps incentives aligned

Common Mistakes to Avoid

Don't: Add complex accounting features
Do: Focus on getting paid fast

Don't: Build payment processing from scratch
Do: Use Stripe (PCI compliance alone takes 8+ weeks)

Don't: Require accounting knowledge
Do: Make it usable by anyone

7. Property Viewing Scheduler

What It Does

Platform connecting estate agents with potential buyers for property viewings:

• Agents list properties with available viewing slots
• Buyers browse and book viewings instantly
• Automated confirmations and reminders
• Calendar sync for agents
• Viewing management dashboard

Who It's For

Estate agents tired of phone tag scheduling viewings, and buyers who want instant booking.

Build Complexity

3 weeks

Week 1-2:

• Property listings
• Agent profiles
• Viewing slot management
• Buyer booking flow
• Calendar system

Week 3:

• Email/SMS notifications
• Calendar sync (Google Calendar)
• Agent dashboard
• Booking management

Cost

£37,500 (3-week sprint)

Tech Stack

Frontend: Next.jsBackend: Next.js API routes + SupabaseDatabase: PostgreSQL via SupabaseCalendar: Integration with Google Calendar APIEmail/SMS: Twilio for SMS, Resend for emailMaps: Mapbox for property locationsHosting: Vercel

What Made It Work

1. Solves real pain: Agents waste hours playing phone tag

2. Instant gratification: Buyers can book viewing immediately (like booking restaurants)

3. Two-sided benefit: Agents get more viewings with less effort, buyers get convenience

4. Mobile-optimised: Most buyers browse properties on phone

Results

• 80 estate agents signed up (London area)
• 1,200 viewings booked in first 2 months
• 15% conversion to offers (very high)
• £49/month per agent
• Clear ROI for agents (2-3 extra viewings per month pays for itself)

Two-Sided Platform Insights

Cold start strategy:

1. Partnered with 3 estate agents initially
2. Added all their properties
3. Drove buyers via property portals (Rightmove ads)
4. Once booking volume proved value, approached more agents

Key metrics:

• Viewings per property (higher = agents happy)
• Booking-to-offer conversion (proves quality)
• Agent time saved (sell the efficiency gain)

Common Mistakes to Avoid

Don't: Try to replace full estate agent software
Do: Solve one problem really well (viewing scheduling)

Don't: Charge buyers
Do: Charge agents (they have the budget, capture the value)

Don't: Build complex CRM features
Do: Integrate with existing systems (Google Calendar)

8. Meal Prep Planning App for Gyms

What It Does

White-label nutrition app for gym owners:

• Clients get personalised meal plans
• Macro tracking
• Shopping lists
• Recipe database
• Progress tracking
• Direct chat with trainer

Who It's For

Gym owners who want to offer nutrition coaching without hiring nutritionists.

Build Complexity

2 weeks

Week 1:

• Meal plan generator
• Recipe database
• Macro tracking
• Shopping list generation
• Mobile app

Week 2:

• White-labelling (gym branding)
• Trainer-client chat
• Progress tracking
• Push notifications

Cost

£25,000 (2-week sprint)

Tech Stack

Frontend: React Native (Expo)Backend: SupabaseDatabase: PostgreSQL via SupabaseAI: OpenAI GPT-4 for meal plan generationReal-time Chat: Supabase real-timeHosting: Supabase + Expo

What Made It Work

1. B2B2C model: Sell to gyms (B2B), they give to clients (B2C)

2. White-label: Each gym's clients see gym branding, not platform branding

3. Trainer stays in control: Trainers review and approve meal plans

4. Adds recurring revenue for gyms: £5-10/month per client

Results

• 8 gyms using it (500-2,000 members each)
• 1,200 active client users
• £99/month per gym + £2/active client
• Gyms charge clients £10-15/month (good margin for them)
• Win-win-win (platform, gym, client all benefit)

White-Label Approach

Technical implementation:

• Single codebase
• Gym-specific branding via config
• Separate data per gym
• Custom domain per gym (optional)

Why it works:

• Gyms look professional
• Clients trust their gym brand
• Platform stays behind scenes

Common Mistakes to Avoid

Don't: Sell direct to consumers (hard to acquire)
Do: Sell to gyms with existing audiences

Don't: Charge gyms per-client from day 1
Do: Low base fee + usage pricing (aligns incentives)

Don't: Build custom nutrition algorithms
Do: Use GPT-4 with nutrition database (faster, cheaper)

Book a free discovery call to discuss your B2B app idea.

9. Code Snippet Manager for Developers

What It Does

Personal code snippet library with AI-powered search:

• Save code snippets with tags
• AI-powered search ("How do I handle auth in Next.js?")
• Syntax highlighting for 50+ languages
• Share snippets with team
• Browser extension for quick save
• CLI for terminal access

Who It's For

Developers who constantly Google the same things or save snippets in random text files.

Build Complexity

2 weeks

Week 1:

• Snippet creation and management
• Tagging and categorisation
• Search functionality
• Web interface
• Syntax highlighting

Week 2:

• AI-powered semantic search
• Browser extension (Chrome/Firefox)
• CLI tool
• Team sharing features

Cost

£25,000 (2-week sprint)

Tech Stack

Frontend: Next.jsBackend: Next.js API routesDatabase: PostgreSQL via SupabaseVector DB: Supabase pgvector for semantic searchAI: OpenAI embeddingsBrowser Extension: Chrome Extension APICLI: Node.js CLI toolHosting: Vercel

What Made It Work

1. Developers are willing to pay: If it saves time, devs will pay £10-20/month

2. Multiple interfaces: Web, browser extension, CLI (developers love CLI)

3. AI search understands code: Can search by what code does, not just keywords

4. Team features: Share common snippets across team

Results

• 1,800 developers signed up
• 72% active weekly (save at least 1 snippet)
• Average 47 snippets per user
• £12/month for premium (unlimited snippets, AI search, team features)
• 28% conversion to paid (very high)

Developer Tool Insights

Free tier is essential:

• 50 snippets free
• Let developers try it and get hooked
• Premium is "unlock" not "start paying"

CLI matters for adoption:

• 45% of usage is via CLI
• Developers live in terminal
• Browser extension for saving, CLI for retrieving

Common Mistakes to Avoid

Don't: Charge from day 1
Do: Generous free tier, paid is for power users

Don't: Web-only
Do: CLI and browser extension (meets devs where they are)

Don't: Complex organisation systems
Do: Simple tags + AI search (AI handles organisation)

10. Client Portal for Agencies

What It Does

White-label client portal for digital agencies:

• Project updates and progress
• File sharing and approvals
• Invoice and payment management
• Client messaging
• Project timeline
• Deliverable tracking

Who It's For

Digital agencies (design, development, marketing) who want professional client communication.

Build Complexity

3 weeks

Week 1:

• Project management
• File upload and sharing
• Client messaging
• Basic dashboard

Week 2:

• Invoice integration
• Payment processing via Stripe
• Approval workflows
• Timeline views

Week 3:

• White-labelling
• Custom domains per agency
• Agency admin dashboard
• Client permissions

Cost

£37,500 (3-week sprint)

Tech Stack

Frontend: Next.jsBackend: Next.js API routes + SupabaseDatabase: PostgreSQL via SupabaseFile Storage: Supabase StoragePayments: StripeEmail: ResendHosting: Vercel

What Made It Work

1. Replaces email chaos: Everything in one place, not scattered emails

2. Professional image: Agencies look more established with branded client portal

3. Reduces admin: Automated invoicing, payment reminders, file organisation

4. Recurring revenue: £99-299/month per agency depending on client count

Results

• 45 agencies using it
• Average 12 clients per agency
• £6,000+ MRR
• Agencies report 5-8 hours saved per week
• Strong retention (agencies hate switching tools)

B2B SaaS Insights

Pricing strategy:

• Base: £99/month (5 clients)
• Growth: £199/month (20 clients)
• Agency: £299/month (unlimited clients)

Why this works:

• Agencies with few clients pay less
• Growing agencies pay more (can afford it)
• Enterprise clients pay most (get most value)

Common Mistakes to Avoid

Don't: Build full project management
Do: Focus on client-facing features only

Don't: One-size-fits-all branding
Do: White-label so each agency looks unique

Don't: Charge per end-client
Do: Charge per agency with usage tiers

What These Examples Teach Us

1. Narrow Focus Wins

Products that worked:

• Mobile CRM for tradespeople (not "all small businesses")
• Booking for dog groomers (not "all local services")
• Invoice for freelancers (not "full accounting software")

Lesson: Specific > generic. Pick one user type, solve their problem extremely well.

2. Use Existing AI APIs

Every AI product used:

• OpenAI (Whisper, GPT-4, Embeddings)
• Anthropic (Claude)

None built custom models.

Lesson: Don't spend 8+ weeks training models. Use APIs, ship fast, validate first.

3. Managed Services Save Weeks

What we never build custom:

• Authentication (Supabase Auth, Clerk)
• Payments (Stripe)
• Email (Resend, SendGrid)
• File storage (Supabase Storage)
• Hosting (Vercel, Railway)

Lesson: Every custom-built service adds 1-4 weeks. Use managed services unless absolutely necessary.

4. Mobile-First or Web-First?

Mobile products:

• Habit tracking (on-the-go usage)
• CRM for tradespeople (always on-site)
• Meal prep (cooking in kitchen)

Web products:

• Document analyser (sitting at desk)
• Knowledge base (work context)
• Code snippet manager (development work)

Lesson: Build for where users actually are when they need it.

5. B2B vs B2C Pricing

B2C products: £5-25/month (must be affordable for individuals)

B2B products: £99-299/month (businesses have budgets, value time savings)

Lesson: B2B can charge more if you save time/money. B2C must be impulse-purchase price.

6. Speed to Market Matters

All products launched within 2-4 weeks.

Products that validated:

• Had 50+ users within Week 3
• Clear usage patterns by Week 4
• Payment validation by Week 6

Lesson: Longer build times = more risk, higher costs, often no better outcomes.

Can You Build Any of These?

Yes. Here's what you need:

For 1-Week Sprint (£12,500)

Good candidates:

• Simple web apps with CRUD operations
• AI tools using existing APIs
• Mobile apps with straightforward features
• Single-user productivity tools

Requirements:

• Clear core workflow
• No payment processing
• No complex multi-user features
• Can use managed services for everything

For 2-Week Sprint (£25,000)

Good candidates:

• Mobile apps with backend
• AI-powered tools with custom features
• Apps with payment integration
• Multi-user productivity tools
• Simple marketplaces (one transaction type)

Requirements:

• Well-defined scope
• Complexity in 1-2 areas only
• Modern tech stack acceptable

For 3-4 Week Sprint (£37,500-£50,000)

Good candidates:

• Two-sided marketplaces
• B2B SaaS with team features
• Complex AI implementations (RAG, multi-step)
• Products requiring multiple integrations

Requirements:

• Can be built in phases
• Willing to launch with core features only
• Can add advanced features post-validation

What You Can't Build in MVP Sprint

Projects requiring 8+ weeks:

• Custom ML models from scratch
• Blockchain/crypto infrastructure
• Video streaming platforms
• Complex fintech with regulatory requirements
• Enterprise software with SSO, SAML, advanced permissions
• Hardware integration
• VR/AR applications

These need different approach (either longer timeline or phased development).

How to Know If Your Idea Can Be an MVP Sprint

Ask yourself:

1. Can I describe core workflow in under 60 seconds?

Yes → Probably sprintable
No → Too complex, simplify first

2. Can users get value in first session?

Yes → Probably sprintable
No → Too much onboarding, simplify

3. Can I build it with modern managed services?

Yes → Probably sprintable
No → Might need custom architecture (longer timeline)

4. Is it one thing done extremely well or many things done okay?

One thing → Definitely sprintable
Many things → Cut scope dramatically

5. Do I need custom ML, blockchain, or hardware integration?

No → Probably sprintable
Yes → Need different approach

6. Will 50 beta users give me meaningful validation data?

Yes → Sprint makes sense
No → Need different validation approach

Ready to Build Your MVP?

Book a free 30-minute discovery call and we'll:

• Review your product idea
• Tell you honestly if it's sprint-suitable
• Estimate timeline (1, 2, or 4 weeks)
• Show similar examples we've built
• Give you realistic cost and timeline

Book your free discovery call

Come prepared with:

• Core workflow description (60 seconds)
• Target user (specific, not generic)
• Similar products (what exists, what's missing)
• Any user validation you've done

No sales pressure. If your idea needs 8+ weeks, we'll tell you honestly.

Bottom Line

10 products, 10 real examples, same pattern:

1. Specific target user
2. One core problem solved extremely well
3. Built fast (1-4 weeks)
4. Modern tech stack (managed services)
5. Tested with real users immediately
6. Validated before adding polish

Costs:

• 1 week: £12,500
• 2 weeks: £25,000
• 3 weeks: £37,500
• 4 weeks: £50,000

What they all had in common: Launched fast, validated early, iterated based on real usage.

What none of them did: Spend 6 months building in isolation, launch publicly without testing, add every feature before validation.

See what you can build in your next sprint.

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