The Transients Classification Pipeline (TCP) is a Berkeley-led project which federates data streams from multiple surveys and observatories, classifies with machine learning and astronomer defined science priors, and broadcasts sources of interest to various science clients (using the VOEvent protocol). The TCP is a production-level project, being developed to handle several upcoming data torrents (e.g. from the Palomar Transient Factory), and should be scalable to LSST volumes.