The client sought to optimize its dealer onboarding process by automating repetitive tasks and improving operational efficiency to better serve both dealers and customers.

The client was struggling to manage its growing transaction volume. Its current system couldn’t handle high-frequency transactions, and the costly data warehouse lacked scalability. They needed a robust, scalable solution capable of processing thousands of transactions per second.

The client wanted to deliver highly accurate, timely product recommendations to its users. However, the rapid growth of data from customer reviews, blogs, and forums made it difficult to manually process information fast enough to keep recommendations up to date.

The client aimed to leverage AI-powered solutions to estimate dealership valuations and improve optimize inventory management as well as enhance decision-making for over 18,000 automotive franchise dealerships in the USA.

Client was looking to transform the process of searching and querying a document from their internal document repository containing ~1millions of articles, submissions, legal documents and cases, opinion pieces, judgement etc. to increase the efficiency of the associates in guiding end users.

The client wanted to streamline customer query resolution, reduce delays, and improve overall customer satisfaction. Their goal was to simplify the query process for agents while maintaining high service levels and providing faster responses to customers.

A lending company needed an efficient, accurate way to determine construction progress for loan disbursements. Manual inspections were time-consuming, subjective, and prone to errors, causing delayed payments and increased risk of defaults.