Transcription factors (TFs) bind specifically to TF binding sites (TFBSs) at cis-regulatory regions to control transcription. Hence, it is critical to locate these TF-DNA interactions to understand transcriptional regulation. The availability of datasets generated by chromatin immunoprecipitation followed by sequencing (ChIP-seq) empowers our efforts to predict the specific locations of TFBSs with greater confidence than previously possible by fusing computational and experimental approaches. In this work, we processed ~10,000 public ChIP-seq datasets from nine species to provide high-quality TFBS predictions. After quality control, it culminated with the prediction of ~44 million TFBSs with experimental and computational evidence for direct TF-DNA interactions for 640 TFs in 1,101 cell lines and tissues. These TFBSs were used to predict >183,000 cis-regulatory modules representing clusters of binding events in the corresponding genomes. The high-quality of the TFBSs was reinforced by their evolutionary conservation, enrichment at active cis-regulatory regions, and capacity to predict combinatorial binding of TFs. Further, we confirmed that the cell type and tissue specificity of enhancer activity was correlated with the number of TFs with binding sites predicted in these regions. All the data is provided to the community through the UniBind database that can be accessed through its web-interface (https://unibind.uio.no/), a dedicated RESTful API, and as genomic tracks. Finally, we provide an enrichment tool, available as a web-service and an R package, for users to find TFs with enriched TFBSs in a set of provided genomic regions. UniBind is the first resource of its kind, providing the largest collection of high-confidence direct TF-DNA interactions in nine species.