Hybrid recommendation engine with collaborative filtering and deep learning, delivering 34% CTR increase and $2.8M incremental revenue.
Manual data processing in E-Commerce AI could not scale with the organization\'s growth. They needed an intelligent automation layer to extract insights and predict trends accurately.
We deployed advanced machine learning models to automate feature engineering, provide real-time inference, and boost overall accuracy.
Real-time personalisation AI engine with collaborative filtering, session-based recommendations, A/B testing framework, and e-commerce integration.
Real-time clickstream capture, user preference modelling, recommendation generation, A/B experiment assignment, and conversion analytics.
Every product view, add-to-cart, and purchase event tracked in Redis session store for real-time preference modelling.
Hybrid model (collaborative + content-based) generates top-N product recommendations per user in under 50ms.
Incoming requests assigned to control or treatment variant; recommendations served per assigned experiment arm.
Recommendation clicks, add-to-carts, and purchases attributed to experiment arms for statistical significance analysis.
A battle-tested methodology that turns complex challenges into elegant, high-performance solutions.
Deep-dive into business requirements, user personas, market analysis, and technical landscape assessment.
System architecture blueprints, UI/UX wireframes, interactive prototypes, and design system creation.
Iterative sprints with CI/CD pipelines, code reviews, automated testing, and continuous stakeholder feedback.
Production deployment, performance monitoring, A/B testing, and post-launch growth optimization.
Every solution we build comes packed with enterprise-grade features that ensure reliability, performance, and scalability.
SOC 2 compliant infrastructure with end-to-end encryption and zero-trust architecture.
Auto-scaling cloud infrastructure designed to handle 10x traffic spikes seamlessly.
WebSocket-powered live updates ensuring data consistency across all touchpoints.
Pixel-perfect experiences across all devices, from mobile to 4K displays.
Custom dashboards with real-time KPIs, funnel analysis, and predictive insights.
RESTful & GraphQL APIs enabling seamless third-party integrations and extensibility.
Key architectural decisions, data flow optimizations, and security patterns implemented for enterprise performance.
Two-tower architecture encodes users and items into shared embedding space, enabling approximate nearest-neighbour retrieval in milliseconds.
For new users, session context (current browsing) drives content-based recommendations until collaborative signals accumulate.
FAISS index with IVF quantisation serves approximate nearest-neighbour product lookups across 10M+ products in under 5ms.
We carefully selected a cutting-edge technology stack to ensure maximum performance, maintainability, and future-proof scalability for this project.
"The AI models Techphin deployed reduced our processing time by 60% and improved prediction accuracy to levels we didn\'t think were possible."
Let's transform your idea into a world-class digital product. Our team is ready to bring your vision to life.
Get Free Consultation