Summary. Tissue capture and recovery for molecular analyses such as immunostaining and gene expression analysis is important for gleaning information from tissue blocks relating to disease. The difficulty with existing solutions is that if tissue recovery is envisioned, sectioning and recovering thin tissue sections from target tissues or organs from an entire organism is not possible. Existing solutions provide manual tissue recovery, requiring the operator to be present to determine whether or not to collect a section from a tissue of interest. To address this challenge, BioInVision will bring to market a 3D tissue imaging solution for preclinical applications that em- ploys automatic, deep-learning, on-the-fly target tissue recognition from a whole organism and semi-automated tissue recovery. BioInVision pioneered the CryoVizTM instrument and has successfully commercialized fee-for- service CryoVizTM imaging for over 10 years. Our existing fee-for-service framework is well-adopted and em- braced by 75+ customers and institutions all over the world. High-resolution, broad-fluorescence-support (visible and NIR fluorophores), high-sensitivity block-face CryoVizTM imaging of preclinical frozen tissue blocks creates anatomical brightfield and molecular marker fluorescence 3D microscopic image volumes. AI-based software for deep-learning that will notify the operator in real-time upon encountering tissues of interest in color anatomy, or upon encountering molecular fluorescence such as eGFP cancer cells, enabling further interrogation of these tissues either through ultra-high-resolution tissue imaging (2µm-scale), or semi-automatic tissue capture for his- tological analyses and immunostaining (what we term “image-guided histology”). Semi-automatic tissue capture through speed and temperature control will enable recovery of tissue for molecular analyses. A demonstration project is outlined that involves characterizing whole mice with fluorescent-reporter metastatic cancer cells and fluorophore-tethered cancer targeted imaging agent. Here, we will study distribution of breast cancer metastases throughout the whole mouse and co-localization with immune cells or disease biomarkers. Our solution will also make possible drug delivery studies with fluorescent tracers. It will enable tracking of multiple fluorescently la- beled markers of cell types helping one better understand the tumor micro-environment in cancer biology. It will reduce manual labor and personnel costs and lead to better throughput to enable image-guided histology. This novel solution will cater to a wide variety of application areas including cancer biology, drug delivery, imaging agents and gene expression.