Let me tell you something: building a SaaS product as a solo founder is equal parts thrilling and terrifying. I lived it while creating CoinVault Analytics — and I want to share exactly how I did it: fast, lean, and profitably.

The Origin: Why I Built a Rare Coin Discovery & Valuation SaaS

I’m not just a SaaS builder. I’m also a coin collector — someone who’s obsessed with history, craftsmanship, and the stories behind rare pieces like the 1804 Dollar.

But here’s what drove me to build this: every serious collector and investor I knew was drowning in outdated tools.

They were:

• Using 20-year-old auction catalogs as their primary data source
• Guessing values based on forum posts and hearsay
• Manually tracking provenance across PDFs and spreadsheets
• Missing out on new discoveries because there was no real-time tracking

So I did what any indie hacker would do: I started tracking myself.

For months, I manually logged every auction record — over 1,200 in total. I mapped provenance chains. I tested valuation models. And I realized: this needs to be a product.

Enter CoinVault Analytics — a real-time platform that helps collectors find, authenticate, and value rare coins using AI and data science.

My mission was clear: launch a working MVP in 90 days, with less than $500/month in costs, and do it all on my own.

Defining the Problem: Why This Wasn’t Just Another “Coin App”

• Collectors wanted to know: “Is this coin authentic, or a restrike?” → provenance verification
• Investors asked: “Is this 1804 Dollar overhyped, or a true gem?” → market sentiment analysis
• Auction houses said: “We spend 20 hours a week cataloging coins.” → automated cataloging tools
• Newcomers needed: “How do I even start?” → education + valuation benchmarks

“The newly discovered 1804 Dollar is a type 3 novodel, BUT it’s a beautiful and unmolested product of the US Mint. Imho, this coin is going to bring moon money.”

This collector’s message hit home. I realized: rare coins aren’t just assets — they’re passion projects. My platform had to balance emotion with evidence.

My Lean Tech Stack: Tools That Let Me Build Fast — and Stay Small

As a bootstrapped maker, I couldn’t afford to waste time or money. I needed tools that were:

• Quick to build with (MVP in 90 days)
• Under $500/month (no surprise bills)
• Easy to maintain (I’m a team of one)
• Ready to scale (if users showed up)

After testing a dozen options, I landed on this stack — and it worked.

Frontend: Next.js + Tailwind CSS

I picked Next.js because it’s fast, SEO-friendly, and handles routing automatically. No config headaches. No extra libraries. Just build.

With TypeScript, I caught bugs early. And server-side rendering meant Google could index every coin page — critical for driving organic traffic.

For the UI, Tailwind CSS was a game-changer. I built the entire dashboard in under a week. No design debt. No bloated CSS. Just clean, responsive components.

I used the @tailwindcss/forms and @tailwindcss/typography plugins to make forms and blog posts look sharp — without writing a single line of CSS.

// pages/dashboard.js
import { useState } from 'react';
import { useRouter } from 'next/router';

export default function Dashboard() {
  const router = useRouter();
  const [search, setSearch] = useState('');

  const handleSearch = () => {
    router.push(`/search?q=${encodeURIComponent(search)}`);
  };

  return (
    

      
CoinVault Dashboard
      

         setSearch(e.target.value)}
          className="flex-1 border rounded px-3 py-2"
        />
        
          Search
        
      
    
  );
}

Backend: Supabase (PostgreSQL + Auth + Storage)

Instead of spinning up a full backend, I used Supabase — open-source, free to start, and basically Firebase with serious muscle.

It gave me:

• PostgreSQL to store coin data (year, mint, grade, provenance, auction links)
• Authentication (email, Google, GitHub login — ready in minutes)
• Storage for high-res coin images and auction scans
• Row-level security — each user only sees their own watchlist and alerts

Setting up a new coin record was simple:

// Supabase query: Insert a new coin
const { data, error } = await supabase
  .from('coins')
  .insert([{
    year: 1804,
    denomination: 'Dollar',
    class: 'Type III',
    mint: 'Philadelphia',
    grade: 'MS65',
    provenance: 'James A. Stack Collection (1975)',
    auction_url: 'https://stacksbowers.com/...',
    image_url: 'https://.../1804dollar.jpg'
  }]);

No backend servers. No DevOps. Just straightforward database ops.

AI & Data: Python + FastAPI (for Valuation Engine)

Here’s where things got interesting. I needed a way to estimate a coin’s value — fast, accurately, and with confidence.

So I built a lightweight valuation microservice using Python + FastAPI, hosted on Render for $7/month.

It pulls from:

• Historical auction data (from Stack’s Bowers, Heritage, PCGS)
• Sentiment analysis (using Hugging Face’s twitter-roberta-base-sentiment-latest)
• XGBoost price prediction models (trained on 1,200+ real sales)

The API returns a clear, human-ready response:

// Python: Coin valuation API
from fastapi import FastAPI
import pandas as pd
from xgboost import XGBRegressor

app = FastAPI()
model = XGBRegressor()
model.load_model('coin_valuation_model.json')

@app.post('/predict')
def predict(coin: dict):
  df = pd.DataFrame([coin])
  prediction = model.predict(df)
  return {
    "estimated_value": float(prediction[0]),
    "confidence_score": 0.92,
    "market_trend": "bullish" if prediction[0] > df['last_auction_price'].mean() else "bearish"
  }

Users see: “This coin is likely worth $420K–$510K (92% confidence). Market trend: bullish.”

Hosting & DevOps: Vercel + GitHub Actions

– Vercel hosts the frontend — free, with edge caching and instant deploys
– GitHub Actions runs tests and deploys on every push to main
– Supabase CLI handles database migrations — version-controlled and safe

Total MVP cost: $397/month (Vercel: $0, Supabase: $25, Render: $7, Domain: $15, Email: $10, Analytics: $50, Monitoring: $50, Buffer: $250).

No cloud bill surprises. No over-provisioning. Just lean, efficient infrastructure.

Product Roadmap: From MVP to Scalable Platform

I didn’t plan everything upfront. I followed a lean product roadmap — focusing on what users actually needed, not what tech looked cool.

Phase 1: MVP (0–90 Days)

• Search and provenance lookup (the core value)
• Basic valuation engine (regression-based)
• User accounts + saved watchlists
• Blog with educational content (for SEO and trust)

Phase 2: Monetization (91–180 Days)

• Freemium model: Free for search, $29/month for valuation + alerts
• API access for auction houses — $99/month for bulk data
• Custom alerts (e.g., “Notify me when a Class I 1804 Dollar hits the market”)

Phase 3: Scale (6–12 Months)

• Mobile app (React Native — responsive, not native-feel)
• Blockchain-based provenance tracking (on Ethereum L2 for low gas fees)
• AI image recognition (upload a photo, get a match and valuation)
• Partnerships with PCGS and NGC for verified grading data

Getting to Market Faster: Lean Startup Tactics That Worked

Here’s the real secret: I didn’t build first. I validated first.

1. Pre-Sell the MVP

Before writing a single line of code, I built a simple landing page with a waitlist and pricing tiers.

I shared it on Reddit (r/coins), Indie Hackers, and Twitter. Within 3 weeks, I had 67 pre-sales at $29/month — $1,943 in committed revenue.

That validated demand. It funded development. And it became my North Star.

2. Use “Fake Door” Testing

For the valuation feature, I built a “fake door”: users could click “Get Valuation,” but instead of AI, I manually replied with estimates within 24 hours.

This let me:

• Test UX without building the model
• Collect real user data (what coins they valued, why)
• Build trust through responsiveness

By the time I built the real engine, I knew exactly how users wanted to see the results.

3. Scrape Existing Data (Ethically)

I scraped 1,200+ auction records from Stack’s Bowers, PCGS, and Heritage — always respecting robots.txt and ToS.

I cleaned the data with Python, normalized grades (PCGS, NGC, Sheldon), and seeded the database. Users got value on day one — no empty platform syndrome.

4. Build in Public

Every week, I posted progress on Twitter and Indie Hackers.

I shared:

• Screenshots of the dashboard
• Code snippets (like the valuation API)
• User feedback and pricing experiments

This drove early signups. It attracted a CTO co-founder who loved the mission. And it built a community around the product before launch.

Bootstrapping Lessons: Cash Flow > Cool Tech

As a solo founder, I learned one truth fast: cash flow beats cool tech every time.

• I delayed blockchain until we had $10K MRR — no need to burn money on hype
• I used open-source tools (Supabase, Tailwind, Hugging Face) to cut costs
• I outsourced design and copy on Fiverr — $50 for a logo, $100 for a homepage rewrite
• I focused on monetization early — I said no to VC offers. I wanted control, not cash

This wasn’t about building the most advanced AI. It was about building something people paid for.

Conclusion: The SaaS Playbook for Niche Markets

Building a SaaS in a niche market like rare coins isn’t about copying Shopify or Airbnb. It’s about domain expertise + lean execution.

1. Start with a real problem (e.g., “How do I verify this 1804 Dollar is authentic?”)
2. Build a lean tech stack (Next.js + Supabase + Python microservices)
3. Validate demand before coding (pre-sell, fake doors, waitlists)
4. Launch fast, iterate faster (90-day MVP, then add monetization)
5. Monetize early, stay bootstrapped (freemium + API access)

Today, CoinVault Analytics has over 1,400 users, $18K in monthly recurring revenue, and is on track to hit $50K MRR this year.

And yes — we’re already tracking the newly discovered 1804 Dollar from the James A. Stack collection. The one that “will bring moon money.”

The lesson? You don’t need a $100K seed round to build a profitable SaaS. You need a real problem, a lean stack, and the courage to ship.

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