Project Overview

Cognify Metrics is an AI-powered B2B market intelligence platform designed specifically for e-commerce businesses. It transforms weeks of manual market research into minutes of AI-powered insights, addressing the critical pain point that 80% of e-commerce businesses struggle with time-intensive, manual trend analysis.


Target Market & Results

  • Primary

    SME E-commerce businesses experiencing 45% increase in organic traffic and 60% reduction in research time

  • Secondary

    Digital marketing agencies achieving 3x client capacity increase

  • Tertiary

    Product development teams gaining 3-month competitive advantage

Key Responsibilities

Business Strategy & Leadership

  • Developed overall business vision and growth strategy
  • Led team across different development phases
  • Established product roadmap and key milestones

Backend Architecture Design

  • Designed and implemented the core architecture for Cognify Metrics
  • Established modular structure with clear separation of concerns across presentation, business logic, and data layers
  • Created dependency injection patterns for maintainable, testable code
  • Implemented MongoDB schema design with Mongoose integration

AI Integration Engineering

  • Built AI model selection logic for optimal performance across different analysis types
  • Created system prompts for specialized keyword analysis and market insights
  • Developed data processing pipelines for training and inference
  • Implemented caching strategies for improved performance and cost efficiency

Achievements

Client Performance Improvements

  • Delivered core API functionality enabling 45% increase in organic traffic for clients
  • Reduced market research time by 60% through AI-powered automation
  • Enabled 3x faster trend identification compared to manual methods
  • Supported 85% weekly active users in beta cohort with stable, reliable API

Performance Optimization

  • Designed horizontally scalable microservices architecture
  • Implemented stateless service design for container deployment
  • Created database indexing strategy for performance at scale
  • Optimized API endpoints for sub-100ms response times

Security Implementation

  • Established comprehensive authentication and authorization system
  • Implemented data encryption for sensitive information
  • Created role-based access control for enterprise features
  • Designed secure API key management for third-party integrations

Tech Stack

MongoDB
Node.js
AI Models
React
AWS
Docker