Case Studies

Results That Speak

Ecommerce

JUST PET BD

Ecommerce & Brand Growth

Challenge

No digital presence for pet products in Bangladesh. Manual order handling, no brand trust, and zero online visibility.

Strategy

Build a full-stack ecommerce platform with Meta Ads funnel, server-side tracking, and verified business presence.

Execution

Developed Next.js storefront with MongoDB backend, integrated Meta Pixel + CAPI, set up WhatsApp automation, and achieved BM verification.

Result

Verified BM, automated order flow, active customer base, and consistent monthly revenue growth.

Next.jsNode.jsMongoDBMeta CAPIVPSWhatsApp API
3x
Revenue Growth
100%
Order Automation
Yes
BM Verified
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JUST PET BD
Ecommerce Platform

City Pet Shop

Pet Ecommerce System

Challenge

Need for a multi-city pet marketplace with real-time inventory, delivery integration, and payment processing.

Strategy

Design a scalable multi-vendor architecture with PostgreSQL, Prisma ORM, and Stripe payments.

Execution

Built Next.js frontend with role-based dashboards, integrated delivery APIs, and deployed on optimized VPS with CDN.

Result

Multi-city operations with integrated logistics, automated payments, and vendor onboarding system.

Next.jsPostgreSQLPrismaStripeVPSTailwind CSS
5+
Cities Active
20+
Vendors Onboarded
99.9%
Uptime
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City Pet Shop
SaaS / AI Tool

FreshRemoveBG

AI Background Removal SaaS

Challenge

Existing tools are expensive or slow. Need a freemium SaaS that processes images fast and converts free users to paid.

Strategy

Build an AI-powered background removal tool with AWS Lambda for processing, Next.js frontend, and Stripe billing.

Execution

Developed Python/OpenCV backend, serverless image processing pipeline, credit-based billing, and responsive Next.js UI.

Result

Processing thousands of images monthly with healthy freemium-to-paid conversion rate.

Next.jsPythonOpenCVAWS LambdaStripePostgreSQL
10K+
Images/Month
<2s
Processing Speed
8%
Conversion Rate
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FreshRemoveBG
Security SaaS

Fraud Detect

Security & Fraud Detection Platform

Challenge

Digital fraud is rising in online transactions. Need real-time detection with high accuracy and low false positives.

Strategy

Build ML-powered fraud detection API with explainable results, dashboard, and webhook alerts.

Execution

Trained TensorFlow model on transaction datasets, built REST API with Python/FastAPI, Next.js dashboard, and Docker deployment.

Result

Real-time fraud scoring with 95%+ accuracy, enterprise dashboard, and alert system.

Next.jsPythonTensorFlowFastAPIPostgreSQLDocker
95%+
Accuracy
<100ms
Detection Speed
<3%
False Positive
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Fraud Detect
1
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