Pollinators are imperiled by global declines that can impair plant reproduction, erode essential ecosystem services and resilience, and drive economic losses. Monitoring pollinator biodiversity trends is key for adaptive conservation and management, but conventional surveys are often costly, time consuming, and require taxonomic expertise. Environmental DNA (eDNA) metabarcoding surveys are booming due to their rapidity, non-invasiveness, and cost efficiency. Microfluidic technology allows multiple primer sets from different markers to be used in eDNA metabarcoding for more comprehensive species inventories whilst minimizing biases associated with individual primer sets. We evaluated microfluidic eDNA metabarcoding for pollinator community monitoring by introducing a bumblebee colony to a greenhouse flower assemblage and sampling natural flower plots. We collected nectar draws, flower swabs, or whole flower heads from four flowering species, including two occurring in both the greenhouse and field. Samples were processed using two eDNA isolation protocols before amplification with 15 primer sets for two markers (COI and 16S). Microfluidic eDNA metabarcoding detected the target bumblebee and greenhouse insects as well as common regional arthropods. Pollinator detection was maximized using whole flower heads preserved in ATL buffer and extracted with a modified Qiagen® DNeasy protocol for amplification with COI primers. eDNA surveillance could enhance pollinator assessment by detecting protected and endangered species and being more applicable to remote, inaccessible locations, whilst reducing survey time, effort, and expense. Microfluidic eDNA metabarcoding requires optimization but shows promise in revealing complex networks underpinning critical ecosystem functions and services, enabling more accurate assessments of ecosystem resilience.