Structural building data inside planning applications is crucial for commercial real estate and for investment decisions, whether to buy, sell or purpose a property. Investment returns and performance directly correlate to the speed of access to quality planning data. This highly innovative project proposes the automation of extraction tasks of planning information using artificial intelligence, especially machine learning and natural language processing. Honest AI technology searches and analyses thousands of images and PDFs, and by contextual understanding the content of the search query, it analyses and matches this information with relevant data in extracted images and PDFs and gives the answer back to the user. The system will facilitate the workflow/task automation of knowledge workers in commercial real estate firms by understanding the information needs of the users based on previous behaviour and feedback given. The solution, accessed directly within our previously developed enterprise search platform for commercial real estate data, will be offered as an add-on feature. It will help commercial real estate investors, underwriters and eveloperers to accelerate property analysis as well as avoid manual data entry into corporate systems and analysis tools, allowing them to focus on higher-value tasks. It will generate significant cost savings of up to 30% through the reduction of the time spent on manual tasks. In addition to that, we expect significant operational risk reduction, which will lead to reduced cost of mistakes as well as additional transparency in decision making across all stakeholders.