ZENFLOWS AI Mail Automation Software is an AI-driven email response system that automates customer interactions and manages incidents requiring manual intervention. It leverages OpenAI GPT-3.5 Turbo, trained on FAQs with semantic similarity matching, to provide accurate responses.

Emails with low AI confidence scores are flagged for manual review, ensuring accuracy. The system securely integrates with Gmail, Outlook, and IMAP/SMTP using OAuth 2.0. Additionally, AfterShip API integration automates order tracking responses, while a React.js-based dashboard offers real-time analytics on AI performance. Subscription-based plans are managed via Stripe integration.

The platform is a HIPAA-compliant, AI-driven diagnostic test management system designed to digitize and streamline the end-to-end lifecycle of diagnostic reports—starting with Pulmonary Function Tests (PFTs). It enables testing clinicians, physicians, and administrators to seamlessly upload, interpret, review, and sign diagnostic reports within a single secure environment.
The system aims to reduce physician workload through AI-generated interpretations, while preserving clinical authority, regulatory compliance, and full traceability. It incorporates state-based physician licensing controls to ensure that reports are routed only to authorized physicians as mapped by administrators.

The primary objective of this project is to design and implement an event-driven backend system that automates the generation, validation, and delivery of healthcare-related EDI (Electronic Data Interchange) files, such as 834 (Eligibility and Enrollment), 837 (Claims), and 835 (Remittance Advice). These files are essential for secure, standardized, and compliant data exchange between healthcare providers, payers, and regulatory partners.

This system aims to:

• Ensure compliance with HIPAA and EDI X12 standards through rigorous validation (via Cotiviti).
• Enable seamless integration with external vendors like Avesis, Nations Benefits, and Reveleer through SFTP-based delivery mechanisms.
• Maintain operational transparency and traceability using real-time monitoring and logging via SigNoz.
• Support future scalability and workflow orchestration through modular design and integration with AWS services like SQS and Step Functions.