Business value provided to the client by-

• Carrying out comprehensive testing via pattern-based comparison of data between source and target and accommodates transformation rules within data patterns. The robust Pattern Learning and multiple testing iterations identifies the Inter-systems gaps.

• To put AI into action, all results generated by the algorithms are supported by auditable “facts” and not based solely on a probabilistic model.

• The tool can be easily integrated with healthcare customized NLP to extract issues in provider network directories

• The implementation centric ML engine finds the incorrect networks, shows the root cause and provides solution by adding the right network values provided from NLP

• The platform’s algorithms run on a powerful, statistical, multi-model and self-learning engine to identify data errors, with minimal manual input