20-Day Startup Launch: Complete Case Study - From Idea to ₹1.5L MRR

"Can you really launch a startup in 20 days?" Everyone asks this. So here's the complete, unfiltered case study of LAW-AI—a legal tech startup that went from idea to ₹1.5L monthly recurring revenue in just 20 days. Every detail, every challenge, every win.

The Idea: Legal Research is Broken

The founder, Amit (name changed), is a practicing lawyer in Delhi. He was spending 4-5 hours daily on legal research—reading case laws, finding precedents, analyzing judgments. It was tedious, time-consuming, and expensive.

His idea: Use AI to automate legal research. Upload a case brief, get relevant case laws, precedents, and legal arguments in minutes instead of hours.

The Challenge: He had zero technical background and a limited budget (₹3L total). He needed to launch fast to validate the idea before investing more.

Day 0: The Kickoff Call

Date: January 1, 2025
Duration: 2 hours
Outcome: Clear scope and timeline

We started with a detailed discovery call. Amit explained his vision, pain points, and target users. We asked tough questions:

• Who exactly will use this? (Solo practitioners, law firms, corporate lawyers)
• What's the core value? (Save 3-4 hours daily on research)
• What can wait? (Mobile app, advanced analytics, multi-language)
• What's the budget? (₹2.5L for development, ₹50K for marketing)

Key Decision: We decided to build a web-based MVP with 8 core features. No mobile app, no fancy design—just functional and fast.

Days 1-3: Planning & Architecture

Day 1: User Flows & Wireframes

We mapped out 3 critical user journeys:

1. Lawyer uploads case brief → AI analyzes → Returns relevant case laws
2. Lawyer searches for specific legal topic → Gets precedents and arguments
3. Lawyer saves research → Organizes in folders → Exports as PDF

Created low-fidelity wireframes in Figma. No colors, no fancy UI—just boxes and text. Amit approved in 3 hours.

Day 2: Technical Architecture

Tech Stack Chosen:

• Frontend: Next.js 14 + React + Tailwind CSS
• Backend: Next.js API routes + Node.js
• Database: PostgreSQL (for structured legal data)
• AI: OpenAI GPT-4 + Custom legal knowledge base
• Authentication: NextAuth.js
• Payments: Razorpay
• Hosting: Vercel (frontend) + AWS RDS (database)

Day 3: Development Environment Setup

• Set up Git repository
• Configured development and staging environments
• Set up database schema
• Integrated OpenAI API
• Created project documentation

Days 4-12: Core Development Sprint

Days 4-5: Authentication & User Management

Built:

• Email/password registration and login
• Email verification system
• Password reset functionality
• User profile management
• Session management

Challenge: Legal data is sensitive. We implemented extra security measures—encrypted passwords, secure sessions, HTTPS only.

Days 6-8: AI Legal Research Engine

This was the core feature. We built:

• Document upload system (PDF, DOCX)
• Text extraction and processing
• GPT-4 integration for legal analysis
• Custom prompts for Indian legal context
• Case law database integration
• Results ranking algorithm

Challenge: GPT-4 doesn't know Indian law well. We created a custom knowledge base with 1000+ Indian case laws and trained the AI to reference them.

Result: 85% accuracy on test cases. Good enough for MVP.

Days 9-10: Research Management & Organization

• Save research results
• Create folders and categories
• Search saved research
• Export to PDF with formatting
• Share research with colleagues

Days 11-12: Payments & Subscriptions

Pricing Model:

• Free: 5 searches/month
• Pro: ₹2,999/month (unlimited searches)
• Firm: ₹9,999/month (5 users, unlimited searches)

Integrated Razorpay for payments. Set up subscription management, billing portal, and invoice generation.

Days 13-16: Polish & Admin Features

Days 13-14: Admin Dashboard

Built admin panel for Amit to:

• View all users and their activity
• Monitor AI usage and costs
• Manage subscriptions
• View revenue metrics
• Handle support tickets

Days 15-16: Email Automation & Notifications

• Welcome email sequence
• Research completion notifications
• Subscription renewal reminders
• Usage limit warnings
• Weekly digest emails

Days 17-19: Testing & Bug Fixes

Day 17: Internal Testing

Our team tested every feature. Found 23 bugs—mostly UI issues and edge cases.

Day 18: Beta Testing with Real Lawyers

Amit invited 5 lawyer friends to test. They found 8 more issues:

• PDF export formatting was broken
• Search was too slow (fixed with caching)
• Some legal terms weren't recognized
• Mobile view had layout issues

Fixed all critical bugs. Documented minor issues for post-launch.

Day 19: Performance Optimization

• Optimized database queries (50% faster)
• Added caching for common searches
• Compressed images and assets
• Implemented lazy loading
• Set up CDN for static files

Result: Page load time reduced from 3.2s to 1.1s.

Day 20: Launch Day! 🚀

Date: January 21, 2025
Time: 10:00 AM IST

Morning: Final Deployment

• Deployed to production (Vercel)
• Configured custom domain (lawai.in)
• Set up SSL certificates
• Configured analytics (Google Analytics + Mixpanel)
• Set up error monitoring (Sentry)
• Final smoke tests

Afternoon: Launch Announcement

Amit announced on:

• LinkedIn (his network of 2000+ lawyers)
• WhatsApp groups (5 legal professional groups)
• Email to 150 contacts
• Bar Association notice board

Evening: First Users!

By 6 PM, we had:

• 23 signups
• 12 active users
• 47 searches performed
• 3 paid subscriptions (₹8,997 revenue!)

Post-Launch: First 60 Days

Week 1 (Days 21-27)

• Users: 67 signups, 34 active
• Revenue: ₹23,991 (8 Pro, 2 Firm subscriptions)
• Feedback: Mostly positive, requested 5 new features
• Issues: 3 minor bugs fixed

Month 1 (Days 21-50)

• Users: 156 signups, 89 active
• Revenue: ₹89,970 (28 Pro, 4 Firm subscriptions)
• Churn: 12% (acceptable for MVP)
• Added 2 requested features

Month 2 (Days 51-80)

• Users: 312 signups, 187 active
• Revenue: ₹1,52,955 MRR (48 Pro, 7 Firm subscriptions)
• Churn: 8% (improving)
• ROI: Recovered ₹2.5L development cost!

Complete Cost Breakdown

Development Costs

• RAGSPRO Development: ₹2,50,000
• Domain & SSL: ₹2,500
• Initial hosting setup: ₹0 (Vercel free tier)
• Total Development: ₹2,52,500

Monthly Operating Costs

• Hosting (Vercel + AWS): ₹8,000
• OpenAI API: ₹15,000
• Email service: ₹2,000
• Payment gateway fees: ₹4,500 (3% of revenue)
• Monitoring tools: ₹1,500
• Total Monthly: ₹31,000

Marketing Costs (First 2 Months)

• LinkedIn ads: ₹25,000
• Google ads: ₹15,000
• Content marketing: ₹10,000
• Total Marketing: ₹50,000

Key Challenges & How We Solved Them

Challenge 1: AI Accuracy for Indian Law

Problem: GPT-4 doesn't know Indian legal system well.

Solution: Created custom knowledge base with 1000+ Indian case laws. Fine-tuned prompts for Indian legal context.

Result: 85% accuracy, good enough for MVP.

Challenge 2: Slow Search Performance

Problem: Initial searches took 8-10 seconds.

Solution: Implemented caching for common queries. Optimized database indexes.

Result: Reduced to 2-3 seconds.

Challenge 3: High AI API Costs

Problem: OpenAI costs were ₹25K/month initially.

Solution: Optimized prompts to use fewer tokens. Implemented smart caching.

Result: Reduced to ₹15K/month.

Lessons Learned

1. Speed Matters More Than Perfection

We launched with 85% accuracy, not 100%. Users were happy because it still saved them 3-4 hours daily. We improved accuracy post-launch based on real feedback.

2. Talk to Users Early

Beta testing on Day 18 caught 8 critical issues. Without it, we would have launched with broken features.

3. Pricing is Hard

We started at ₹1,999/month. Users said it was too cheap and didn't trust the quality. We raised to ₹2,999/month and conversions improved!

4. Focus on One Core Feature

We almost added 5 extra features. Glad we didn't. The AI research engine alone was enough to validate the idea.

Current Status (3 Months Post-Launch)

• Users: 500+ signups, 280+ active
• Revenue: ₹1,80,000 MRR (growing 15% monthly)
• Churn: 6% (industry average is 10-15%)
• Team: Amit + 1 part-time support person
• Profitability: ₹1,20,000/month profit
• Next Steps: Mobile app, advanced analytics, API for law firms

Can You Replicate This?

Yes, if you:

• ✅ Have a clear problem to solve
• ✅ Know your target users well
• ✅ Can validate the idea quickly
• ✅ Are willing to launch imperfect
• ✅ Have ₹85K - ₹3L budget
• ✅ Can commit to 20 days of focused work