In modern times, business rules have grown exponentially with enterprises becoming more complex in diverse fields. Due to this growth, different forms of anomalies creep into the business rules, causing business enterprise to take wrong decisions, which can impact it's performance and reputation. It is time and resource consuming to examine the rules manually due to the large number of rules intermingled with each other. The process of manual verification is also not free of human induced errors. Thus, automatic verification of business rules is the need of the hour. We present a tool to detect different anomalies in business rules represented in SBVR format. The tool uses a combination of Directed Graphs and SMT solvers to perform the verification task. We show the implementation of our tool along with it's evaluation on industry level benchmarks.
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