Construction Industry is known for its complexity as it involves diverse stakeholders from various levels of business, which oftentimes creates environments where industrial-level data processing and collaboration are restrained by the conflicting interests among the stakeholders. This becomes an issue as data processing serves as an important aspect in managing and monitoring the industryâs performance, as well as providing projections for future strategy. Technology is one of the factors that can advance the industry and requires a strategy for its implementation as it can also bring threats that were not previously known despite its benefits. This study aims to evaluate the strategy of Indonesian construction technology database preparation. The nature of the industry and the availability of data, whose access is limited by the interest of various parties, are some of the considerations used in formulating the database preparation strategy. The study evaluates the strategy of preparing a structured database through available open access data, namely the contractorâs annual report from a public company. The strategy used in this study has transformed unstructured data into a structured database using Python program and Named Entity Recognition (NER). Based on this research, database strategy preparation using NER is considered quite effective and can be further developed by the implementation of custom NER which can specifically detect construction technology. The strategy developed by the research is the first step for constructing a construction technology database and can be used for similar data environments.