The traditional development, deployment and maintenance of conventional software applications require higher quality with shorter time to market cycles to reap the benefits of customer delight. They follow a conventional, explicit and formal representation of the knowledge base which is shared across the stakeholders. Hence, the associated documentation across various stages of SDLC do not cater to any intelligent extraction and interpretation either for downstream applications or for enhancements. This research framework addresses the nuances of converting the existing documentation to an intelligent knowledge representation which can be extracted for effective and efficient utilisation of the artifacts for further improvisation of the software to deliver enhanced tracea-bility to the changing needs of the future growth.