Case Study: Economic Events Company achieves real-time sentiment-driven trading and maximized profits with Ezappsolution

Economic Events Company - Customer Case Study

Economic Events Company, a financial firm tracking how economic events, company performance and social sentiment drive trading behavior, lacked the capability to determine real‑time sentiment across thousands of trades. Ezappsolution delivered a Sentiment Analyzer platform to surface live sentiment signals (buys/sells/hold) using deep learning and TensorFlow so traders could factor social and market sentiment into decision‑making.

Ezappsolution implemented a serverless data lake and ETL pipeline on AWS (Kinesis, S3, Glue, Lambda, Step Functions) feeding TensorFlow models and an AI recommender, plus an AI bot for automated query responses. The solution produced actionable trading signals, dynamically optimized portfolios and stop‑loss settings, automated trading queries, and increased revenue by leveraging reinforcement learning and sentiment‑driven recommendations.