Pathology labs rely on chemical staining to create contrast in tissue slides, a process that is time‑consuming, consumes reagents, and permanently alters samples, limiting the ability to perform additional molecular or imaging tests on the same specimen.

Pictor Labs replaces the chemical staining step with an AI‑driven virtual staining workflow. The system captures the tissue’s intrinsic autofluorescence, registers the image to a deep‑learning model trained on paired unstained and conventionally stained slides, and generates diagnostic‑quality virtual stains such as H&E or IHC in minutes. Because the tissue remains unaltered, the same slide can be re‑stained virtually multiple times, preserving material for downstream molecular assays. The technology integrates with existing slide scanners and can be deployed either on‑premises or via a secure cloud service, allowing labs to maintain full data control while accelerating turnaround times.

Autofluorescence imaging that provides high‑resolution, label‑free capture of tissue structure

Deep‑learning registration and image‑to‑image translation models trained on paired unstained and stained samples

Generation of multiple virtual stains (e.g., H&E, IHC) from a single slide without chemical reagents

Compatibility with major scanner platforms and seamless integration into current digital pathology pipelines

Deployment options include on‑premise processing for full data oversight or cloud‑based service for scalable, hardware‑free operation

Fast processing that produces virtual stains in minutes, reducing workflow latency

Primary customers are molecular pathology laboratories, digitization‑first hospital pathology departments, research institutions, and high‑throughput reference labs seeking tissue‑preserving, rapid staining solutions.