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We present the design and implementation of ADAM, the first adaptive beamforming-based multicast system and experimental framework for indoor wireless environments. ADAM addresses the joint problem of adaptive beamformer design at the PHY layer and client scheduling at the MAC layer by proposing efficient algorithms that are amenable to practical implementation. ADAM is implemented on a field programmable gate array (FPGA) platform, and its performance is compared against that of omnidirectional and switched beamforming based multicast. Our experimental results reveal that: 1) switched multicast beamforming has limited gains in indoor multipath environments, whose deficiencies can be effectively overcome by ADAM to yield an average gain of threefold; 2) the higher the dynamic range of the discrete transmission rates employed by the MAC hardware, the higher the gains in ADAM's performance, yielding up to ninefold improvement over omni with the 802.11 rate table; and 3) finally, ADAM's performance is susceptible to channel variations due to user mobility and infrequent channel information feedback. However, we show that training ADAM's signal-to-noise ratio (SNR)-rate mapping to incorporate feedback rate and coherence time significantly increases its robustness to channel dynamics.