Elphel is a technology company doing research and development in the field of high-performance digital cameras, image processing, 3D imaging and machine learning. Elphel imaging systems are primarily used for for scientific applications that require designs to be user-modifiable at all levels - from the hardware and FPGA code to the system and application software. Since the start of the company in 2001, Elphel was adhering to the FLOSS practice for the code and now applies CERN Open Hardware License to all electronic boards and mechanical CAD files. Elphel cameras are used in many National Laboratories, and universities in USA, European Union and other countries. Elphel cameras were used in Google Books and Google Streetview projects. More than 30 billion images were scanned with NC323L camera for Google Books project. All early high-resolution Google Streetview images were taken with Elphel NC353L camera core. Starting with this project we introduced JP4 – JPEG-based (and so compatible with the standard libraries) image compression that preserves raw Bayer data of the image sensors. Raw Bayer mosaic is a preferred format for image processing including various types of end-to-end DNN. Elphel technology has been referenced in over a hundred scientific publications, and at least six US patent applications that use or reference Elphel products. Since 2012 Elphel has been developing methods of precise camera calibration and designing photogrammetric multiple-view cameras. From 2016 till present we are working on very long range 3D reconstruction and achieved 0.05 pix disparity resolution by combining several technology components developed by Elphel. Elphel is a member of SOSSEC.