Retail and Consumer Services projects.

1. Dynamic pricing


Implement dynamic pricing to optimize sales and profit margins by adjusting prices based on real-time data and market conditions.

Partner company

Online retailer


Price Competitiveness

Maintaining competitive pricing in a fluctuating market.

Inventory Management

Balancing inventory levels with demand to avoid overstock or stockouts.

Profit Optimization

Maximizing profit margins without losing customers to competitors.


AI-Driven Dynamic Pricing Engine

Implemented a dynamic pricing engine using machine learning algorithms to adjust prices in real-time based on demand, competitor pricing, and inventory levels.

Real-Time Data Integration

Integrated data from sales trends, competitor prices, and market demand to inform pricing strategies.

Automated Price Adjustments

Automated the process of price adjustments, ensuring quick and accurate responses to market changes.

Business value delivered

Increased Revenue

Achieved a 15% increase in revenue through optimized pricing strategies.

Improved Profit Margins

Enhanced profit margins by 10% due to more precise price adjustments and better inventory turnover.

Higher Customer Retention

Maintained a high level of customer retention, with a 5% increase in repeat customers, due to competitive and fair pricing.

2. Personalized Travel Recommendations and Experiences


Provide travel companies with an AI strategy and solutions to deliver highly personalized travel recommendations and experiences to customers.

Partner company

Online travel booking platform


Travelers have diverse preferences based on demographics, travel history, budgets etc.

Manually analyzing customer data to extract insights and create personalized experiences is costly and inefficient.

Generic travel recommendations often fail to resonate, leading to poor engagement and conversions.


Developed advanced customer segmentation models using machine learning to cluster travelers based on their preferences and behaviors.

Built recommender systems that provide highly contextual and personalized travel recommendations tailored to each customer segment.

Integrated natural language processing to allow customers to state their preferences and receive tailored recommendations.

Business value delivered

Travel clients saw 35%+ increase in customer engagement from personalized recommendations.

Conversion rates for recommended packages/destinations improved by 15%.

Reduced customer churn by 20% by delivering more relevant and tailored experiences.

Let's innovate together

Contact us to discuss how we can work together to explore the potential of AI for achieving your goals.

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.