The process of event-building---i.e gathering and associating data from multiple sensors or sub-detectors that arises from a common physical event---is used in many fields, including high-energy physics and gamma-ray astronomy. The problem of fault tolerance in event-building is a difficult one, and one that becomes increasingly difficult with higher data throughput rates and increasing numbers of sub-detectors. We draw on biological self-assembly models in the development of a novel event-building paradigm that treats each packet of data from an individual sensor or sub-detector as if it were a molecule in solution. Bonds (analogous to chemical bonds) are defined between data packets using metadata-based discriminants. A database, which plays the role of a beaker of solution, quasi-randomly and continually selects pairs of assemblies to test for bonds, allowing single tiles and small assemblies to aggregate into larger assemblies. During this process higher-quality associations supersede spurious ones. The database thereby becomes fluid, dynamic, and self-annealing rather than static. We will describe lessons learned from early prototypes of the fluid database as well as future directions.