MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202511006312 A) filed by Ramesh Kasver; Suraj Singh; and Raghuveer Sakuru on January 25, 2025, for Zorfp (agentic Ai For Rfp/Tender Creation And Rfp/Tender Response Validation).
Inventors include Ramesh Kasver; Suraj Singh; and Raghuveer Sakuru.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: Abstract: zoRFP (Agentic AI for RFP/Tender Creation and RFP/Tender Response Validation) The present invention pertains to zoRFP, a pioneering platform powered by Agentic Artificial Intelligence (AI) designed to automate and optimize the end-to- end lifecycle of Request for Proposal (RFP) and tendering processes. This platform leverages state-of-the-art natural language processing (NLP) and machine learning (ML) algorithms to address inefficiencies and challenges inherent in traditional procurement workflows. zoRFP begins by capturing user requirements through structured forms, pre-built templates, or document uploads, enabling precise input collection tailored to specific procurement needs. Using these inputs, the platform generates comprehensive, compliant RFP or tender documents that adhere to industry standards, regulatory frameworks, and historical procurement data. The system’s AI models ensure content is dynamically adjusted to align with evolving requirements and best practices. On the response side, zoRFP incorporates an advanced validation engine capable of analyzing and scoring tender submissions against both predefined and adaptive evaluation criteria. By combining rule-based logic and adaptive AI-driven scoring algorithms, the platform ensures unbiased, accurate, and transparent assessments of vendor responses. Comprehensive evaluation reports, generated by the system, provide actionable insights for decision-makers, including top- scoring responses and areas for improvement or clarification. Key features of zoRFP include automated content creation, customizable templates for various industries, AI-enhanced scoring and ranking mechanisms, and built-in collaboration tools for seamless stakeholder communication. The system also incorporates robust security protocols to protect sensitive procurement data, ensuring compliance with local and international standards. Additionally, its scalable architecture supports large-scale tendering operations across diverse sectors. The invention further includes a feedback loop that continuously refines AI models based on user interactions and historical data, ensuring the platform evolves to meet changing procurement needs. By automating manual tasks, improving accuracy, and enhancing efficiency, zoRFP redefines procurement processes, offering significant time and cost savings for organizations while maintaining the highest levels of compliance and operational excellence.
Disclaimer: Curated by HT Syndication.
