Productivity

ZeroInbox

AI-Powered Email Triage System

ZeroInbox is an AI-powered email triage system using leading AI models for near-instant classification, priority scoring, and context-aware response drafting — TypeScript, React, Node.js, PostgreSQL, Redis, and a queue-based architecture that learns from user feedback.

ZeroInbox hero image

// the problem

Challenge

Email overload is a productivity killer—professionals spend 2+ hours daily on email. The core problem is triage: identifying what needs immediate attention versus what can wait. Standard rule-based filters fail because context matters. Building effective email AI requires understanding intent, urgency, and relationships.

// what we built

Solution

ZeroInbox uses leading AI models with proprietary prompting tuned for email classification. Each incoming email is analyzed for sender importance, content urgency, and required action type. The system generates priority scores, category tags, and draft responses when appropriate. A feedback loop continuously improves classification accuracy over time.

// shipped

Key features

  • Real-time email sync via push notifications
  • AI-powered email classification and scoring
  • Context-aware response drafting
  • Sender relationship tracking
  • Custom category rules
  • Batch processing queue
  • Learning from corrections
  • Thread summarization

// stack.json

Tech stack

The exact tools shipping this product in production.

  • TypeScript
  • React
  • AI/ML
  • Email API Integration
  • Node.js
  • PostgreSQL
  • Redis
  • Job Queue

// system.diagram()

Architecture

Queue-based email processing with AI classification and feedback learning

Push webhook Enqueue Process Store result Fetch/action React Inbox frontend Node.js API backend AI Engine ai Email API external PostgreSQL database Redis cache
  • frontend
  • backend
  • ai
  • external
  • database
  • cache

// receipts

Results

  • AI-powered near-instant classification
  • Real-time email sync with push notifications
  • Proprietary priority scoring algorithm
  • Response drafting with context from thread history
  • Continuous learning from user feedback
  • Bulk actions for batch email processing
Leading AI models
AI Model
Near-instant classification
Latency
Real-time push notifications
Sync
Continuous feedback loop
Learning

// faq

Frequently asked questions

What problem does ZeroInbox solve?

Professionals spend 2+ hours daily on email. Rule-based filters fail because context matters — ZeroInbox uses AI to triage by intent, urgency, and relationships, surfacing the 5% of email that actually needs immediate attention.

What is the technology stack?

TypeScript and React on the frontend, Node.js with a Redis-backed job queue on the backend, PostgreSQL for rules and feedback storage, and leading AI models with proprietary prompting tuned for email classification.

How does the AI learn from user feedback?

Every correction a user makes — changing a priority, reclassifying a category, editing a draft reply — is stored and fed back into the prompting and scoring pipeline, so classification accuracy improves continuously for each user.

Does ZeroInbox draft replies automatically?

Yes — when context warrants it, the system drafts a context-aware response using thread history and sender relationship data. Users review and send rather than starting from scratch.

How does real-time email sync work?

Email provider push webhooks hit the Node.js API, which enqueues the message into Redis for the AI engine to process. Classification results are stored in PostgreSQL and streamed to the inbox UI.

// next()

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