eazyPetition Launches AI-Powered USCIS Petition Preparation Platform Following Successful Beta Phase
EAZYPETITION LLC has launched the full version of its AI-powered eazyPetition platform after a successful beta phase. The legal technology solution automates USCIS petition preparation, document processing, and workflow management, helping applicants, employers, and legal professionals complete immigration petitions with greater speed, accuracy, and efficiency.
Announcing the platform's full launch, Amit Gupta, Founder of EAZYPETITION LLC, said that students, information technology professionals, and family members of naturalized United States citizens often face the challenge of repeatedly preparing USCIS petitions over several years to maintain their legal status and work authorization. He stated that eazyPetition addresses this challenge by providing a single platform where users can securely store all supporting documents and either create a new petition or use information from previous petitions to prepare a new application in under 30 minutes.
Preparing USCIS petitions typically requires applicants to collect information from multiple documents, including passports, visas, I-94 records, previous petitions, educational credentials, and employment records. The same information is frequently entered repeatedly across multiple USCIS forms, making the process time-consuming while increasing the risk of errors that may result in Requests for Evidence (RFEs), processing delays, and additional legal expenses.
Stephen D. Marino, Chair of the Board of Directors at EAZYSTAR SYSTEMS Inc., said the transition from a successful beta programme to full availability represents an important milestone for eazyPetition. He said the growing demand for intelligent legal technology is driving the need for platforms that combine artificial intelligence with reliable workflow automation to improve efficiency and consistency in USCIS petition preparation. He added that eazyPetition is well positioned to help individuals, employers, and legal professionals navigate complex USCIS processes with greater confidence.
The platform uses artificial intelligence to extract information from immigration documents and supporting evidence, allowing users to review, verify, and generate print-ready USCIS PDF petitions through a guided workflow. By automating repetitive data entry and streamlining document preparation, eazyPetition enables every stakeholder participating in the petition process to complete their portion of the workflow in less than 30 minutes. During its beta phase, the platform was successfully used by information technology professionals across the United States, helping simplify petition preparation while improving efficiency and accuracy.
The current version of the platform supports offline USCIS petition preparation, allowing completed petitions to be printed, signed, and submitted through existing USCIS filing procedures. To assist users throughout the immigration process, eazyPetition has also developed a library containing more than 200 educational video tutorials that explain petition preparation and filing workflows.
A major technological innovation behind the platform is EPML (Evidence Process Markup Language), a proprietary framework developed to intelligently model immigration evidence and petition workflows. The framework enables the platform to process supporting documents, automate information extraction, and simplify the preparation of complex USCIS petitions.
The platform is being developed by an expanding engineering team in India, leveraging the country's expertise in artificial intelligence, document intelligence, workflow automation, and legal technology to build next-generation solutions for United States immigration. The full commercial availability of eazyPetition marks a significant step in advancing technology-driven immigration petition preparation by combining automation, artificial intelligence, and structured workflow management to improve accuracy, efficiency, and consistency for applicants and legal professionals.

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