Here’s a well-crafted Project Story in Markdown format for your MailMint submission:
📬 Inspiration
Every day, businesses receive hundreds of emails—most of them ignored, lost in spam, or overlooked due to volume. We asked a simple question: "What if every email could become a business decision trigger?"
MailMint was born from that thought—turning emails into actionable intelligence using AI. Whether it's a vendor quote, product offer, or a spoofed phishing attempt, MailMint makes sure you never miss the insights buried in your inbox.
🛠️ How We Built It
We started by integrating Postmark as the inbound email processor and built a webhook system to stream all incoming messages into our backend.
Using Hono.js on Google Cloud Run (GCR) and Docker, we built a scalable API layer with strict Firebase authentication. We designed a flexible schema using MongoDB and Mongoose to store emails, documents, and verifications.
Then came the magic—MailMint’s Upstash-powered background workflow asynchronously triggered a multi-step process:
- Email Classification
- Product & Price Extraction
- Perplexity AI Integration for benchmarking
- Header-level Spoof Checks
- Final Risk Score & Recommendations
🚧 Challenges We Faced
- Designing a pipeline that processes heavy emails while staying performant under Cloud Run's request limits.
- Creating an idempotent Postmark webhook that avoids double inserts.
- Parsing attachments and HTML emails reliably across formats.
- Ensuring spoof detection (SPF, DKIM, DMARC) was precise and didn't flag valid senders.
- Keeping API response fast while delegating heavy logic to background queues.
💡 What We Learned
- How to build asynchronous verification pipelines with fast API responses.
- Leveraging Perplexity AI as a real-time business intelligence engine.
- The power of mixing cloud-native tools like GCS, Upstash, and Docker to move fast with confidence.
- Why even basic email headers can hold critical trust signals.
📦 Built With
perplexitymongoosemongodbpostmarkgcrgoogle-cloud-rundockerhono-js
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