𝗛𝗲𝗮𝗱𝗹𝗶𝗻𝗲: What started as a simple B2C expense tracker has officially pivoted into a fully automated B2B Financial SaaS. Introducing 𝗙𝗶𝗻𝗮𝗻𝗦𝗺𝗮𝗿𝘁.
𝗕𝗼𝗱𝘆: I realized that startup founders and agency owners spend countless hours manually categorizing bank statements and tracking operational costs. I wanted to build a solution that entirely automates this bookkeeping process.
Building the core feature—an "𝐀𝐈 𝐁𝐚𝐧𝐤 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭 𝐏𝐚𝐫𝐬𝐞𝐫"—was one of the toughest technical challenges I’ve faced. I hit a massive roadblock when Next.js 14’s Webpack bundler kept breaking legacy PDF OCR libraries in serverless environments.
Instead of compromising on the feature, I completely re-architected the data pipeline:
• I bypassed Webpack issues by implementing pdf2json on a strict Node.js runtime for secure, server-side text extraction.
• I piped this raw text into Groq’s LLaMA-3.1-8b model using highly optimized system prompts.
• The result? Lightning-fast, deterministic extraction that converts raw PDF text into perfectly structured JSON arrays.
Now, users can drag-and-drop a PDF statement, and the AI instantly categorizes every transaction (Infrastructure, Payroll, Revenue) into a 'pending' staging area.
Once approved, the data flows securely via Drizzle ORM into a Neon PostgreSQL database, updating real-time Recharts dashboards.
𝑻𝒆𝒄𝒉 𝑺𝒕𝒂𝒄𝒌: Next.js App Router, Tailwind CSS, Shadcn UI, Clerk Auth, Drizzle ORM, Neon DB, and Groq SDK.
𝗪𝗵𝗮𝘁'𝘀 𝗡𝗲𝘅𝘁? I am currently looking for my next full-time opportunity as a Full Stack Developer (based in Bangalore or anywhere).
I am also actively taking on 𝗳𝗿𝗲𝗲𝗹𝗮𝗻𝗰𝗲 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀. If you are a founder or agency looking to build scalable, AI-integrated SaaS MVPs without the technical headache, let's connect.
Check out the demo video below to see the AI parser in action!
🔗 Live Project:
https://lnkd.in/gSNu3cAK
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