Introduction: Several occupational health stakeholders in France organize the collection and production of, or compile, data on health and/or occupational exposure. Data from the databases of the Medical Surveillance of Employee Exposure to Occupational Risks (Sumer) survey, the National Network for the Monitoring and Prevention of Occupational and Environmental Diseases (RNV3PE), the Observatory on Trends and Relationships in Occupational Health (Evrest), the MatGéné job-exposure matrices, the “Occupational Diseases” (MCP) surveillance program, the INRS exposure databases (Colchic, Scola, Colphy), the Occupational Prevention Account (C2P), and claims data from the National Health Insurance Fund (Cnam) are used by their respective owners for a variety of purposes. These may include, in particular, improving the reconstruction of workers’ career paths, helping companies better identify and prevent risks, guiding occupational risk prevention policies, documenting the health impact of occupational exposures, or—for expert analysis—detecting emerging occupational health risks. These databases are not designed to be used in conjunction with one another. However, the information they contain—though of different types—can contribute to a better understanding of occupational risks, particularly those related to multiple exposures. Objective: To demonstrate the feasibility of combining the data available in these databases to improve knowledge about multiple exposures in the workplace and to present preliminary findings. Method: The characteristics of the ten databases are examined in context: purpose of data collection or production, population of interest, types of exposures and/or diseases, statistical unit, and classification systems used. The key challenges to be considered for an integrated analysis are presented: the occupational classifications used to code the data and the choice of the level of detail in the data for analysis. A data model that integrates all these sources for the analysis of multiple exposures is proposed. It is based on the assumption that a group of workers of the same sex, performing the same occupation in the same industry, is likely to be exposed to the same hazards and to develop the same diseases. The construction sector was chosen to present examples of concrete results: counts of exposures, co-exposures, and diseases. Results: If all databases were compiled, the results could provide information on more than 25,000 occupational groups, more than 250 exposures, 27,000 exposure pairs, and 500 occupational diseases. In the construction sector, 92 exposures, 3,508 exposure pairs, and 218 diseases were identified. Discussion: These preliminary results demonstrate the complementary nature of the databases and describe how the heterogeneity of the data they contain can be leveraged to provide additional insights into multiple exposure. They also illustrate the scale of the challenge involved in assessing multiple exposure using these data. The main difficulty encountered is the diversity of the technical nomenclatures used, which makes their integration complex. The next steps in this work will consist of identifying appropriate statistical analyses and applying them to the integrated data.