An industrial experience report on model-based, AI-enabled proposal development for an RFP/RFI

Large organizations respond to huge volumes of Request for Proposals (RFP)/ Request for Information (RFI) every year. The process of developing a proposal for an RFP/ RFI is completely manual and time-, effort-, and intellect-intensive. While Model Driven Engineering (MDE) approaches have been popular in downstream Software Development Lifecycle (SDLC) phases to transform the design models into code, there has been a gap in leveraging model-based techniques in document-centric phases of proposal development, requirements analysis, etc. This paper presents an automated proposal development approach for a client-supplied RFP/RFI using a combination of model-based and AI-enabled techniques and describes the case study of its successful deployment to hundreds of presales users across multiple geographies. We explain the Proposal system and report on the experience of deploying the system in the industry, bring out its efficacy, and user feedback, and discuss the lessons learnt.

Automated summary

This paper presents an automated proposal development approach using a combination of model-based and AI-enabled techniques, and discusses the successful deployment and user feedback of the system.