Actionable Dashboards

• Search, view, and interact with data stored
• Perform advanced data analysis
• Visualize your data in a variety of charts, tables, and maps
• Apply machine learning unsupervised models to detect anomaly in data

Requirement

A solution that helps retailers in automating order management and stock replenishment based on season, historical trends, and minimum and maximum stock benchmarks.

Solution

• The system is based on predictive analytics that works on historical data of past orders, seasonal demands, and stock levels to predict the order size for retailers.
• The system is integrated with POS that collects data real-time and automates the order management which avoids under-stock and over-stock scenarios for retailers.
• It will not just help retailers in stock replenishment but also improve the Sales and RoI by predicting sales and stock trends backed by data.

• Container Move Analysis
• Revenue Analysis for shipping fort
• YTD,QTD,MTD Analysis for Terminal

Social Listening

• Real time Twitter sentiments
• Facebook and Instagram sentiments
• Competitive insights
• Top hashtags and Emoji distribution
• Top keywords and word clouds

Requirement

An easy-to-use intelligent application that helps hotel management to automate the audit of cleaning and maintenance work done by external agencies.

Solution

• The application work on image similarity using deep learning based on artificial neural networks.
• The management will take a picture of the premises after cleaning work done by the agency and upload it to the system, which will preserve information by reconstructing the input and fine-tuning to identify similarities between images pre-uploaded images and with latest ones.
• This will help management to automate the housekeeping audit without manual examination of the work done.

Requirement

A fraud detection system helps land-lords identify their properties listed online as available for rent that is already in use by tenants to prevent subletting.

Solution

• The fraud detection system scrape and search the property’s location to match with Google map data and find the proportionate location as most portals do not display exact locations.
• By using the image processing algorithms it compares images available and online property images
• Based on data available, data gathered using web scrappers, and image data the system matches the metrics and finds the similarities between a rented property and with listed property to calculate the probability of fraud by tenants by subletting the rented property.