The logo of a company whose entire job is to make the invisible visible. Fitting that it looks best on a clean white wall.
FDA-cleared software that outlines the lesions hiding inside dense breast tissue - one click, every modality.
A radiologist sits in a dim reading room at 7 a.m., scrolling through a mammogram that looks like a snowstorm. Dense tissue. Bright, busy, beautiful, and very good at hiding the one thing she is looking for. She clicks once. A clean outline appears around a shape she might have squinted past. That click is DeepLook Medical.
DeepLook is an 18-person company in Scottsdale, Arizona, with a product called DL Precise that does something refreshingly unglamorous: it draws a precise line around suspicious objects in a medical image and measures them. No drama, no oracle, no promise to replace the doctor. Just a sharper view of what was already on the screen.
Today that software runs inside the reading rooms of Cleveland Clinic, Mayo Clinic, AdventHealth and Geisinger. The company is past the lonely product-development years and into the part where hospitals actually pay for the thing. Which, in medtech, is the rare and difficult miracle.
Here is the uncomfortable arithmetic. In women with dense breast tissue, standard mammography can miss up to roughly half of cancers. The tissue and the tumor are both white. Asking a human to spot one bright thing inside a field of bright things, thousands of times a week, is a recipe for the kind of miss nobody wants to talk about.
The industry's usual answer has been to throw a bigger black box at it - an AI that says “cancer: 84% confident” and asks the radiologist to take its word. Radiologists, being sensible people, often don't. A score you can't see inside of is hard to trust, and trust is the only currency that matters when a patient is on the table.
That line belongs to Marissa Fayer, who joined DeepLook as an advisor in 2020 and took the CEO seat in 2022, right as the company crossed from “does it work” to “will anyone buy it.” She came with nine years at Hologic and a decade running a medtech commercialization firm - which is to say, she had seen plenty of clever technology die on the way to the clinic.
Her bet was contrarian for an AI-soaked era: skip the hype, ship a tool that fits the radiologist's existing workflow, and let the results do the persuading. DL Precise leans on deterministic shape-recognition algorithms rather than a probabilistic guess engine. Same input, same output, every time. In a field where reproducibility is a regulatory requirement and a clinical conscience, that is a feature, not a limitation.
Fayer also founded HERhealthEQ, a nonprofit working on women's health equity. The throughline is hard to miss: she treats women's health less as a market segment and more as infrastructure that someone simply has to build.
DL Precise overlays on the imaging systems a hospital already owns. The radiologist hovers over a suspicious area, clicks once, and the software segments the object - drawing a clean boundary around it and measuring it. It works across mammography, ultrasound, CT and MRI, so it isn't married to one machine or one vendor.
The detail that wins meetings: there is no new hardware. No rip-and-replace. The software slides into the existing workstation and the existing workflow, which is the difference between a pilot that fizzles and one that turns into a purchase order.
Outline and measure a suspicious object instantly, instead of tracing it by hand.
Mammography, ultrasound, CT and MRI - one tool, not four.
Runs on existing radiology workstations. No new hardware required.
Shape-recognition algorithms give consistent, explainable results - not a mystery score.
A New York metropolitan hospital ran DL Precise and reported a 12% improvement in recall performance, bringing the department into closer alignment with American College of Radiology guidelines. In the same real-world use, the software contributed to catching a cancer that had previously gone undiagnosed. One patient, one save - which is, ultimately, the only unit of measurement that counts.
The orange bar is the problem. The teal and yellow bars are the company's answer to it.
DeepLook doesn't sell alone. Barco embedded DeepLook's AI directly into its diagnostic displays for dense-breast visualization. Blackford Analysis carries DL Precise on its imaging-AI platform. Philips holds a board observer seat. These are the distribution rails that get a small company's software onto a large hospital's screens.
DeepLook's stated mission is to enhance breast cancer detection and improve diagnostic imaging with tools that empower radiologists, providers and patients. Note the verb: empower, not automate. The company is backed by a leadership bench - CFO David Dahn, CTO Alice Raia, a medical and commercial team - but the philosophy is consistent from top to bottom. The radiologist stays in the chair. The software just makes the chair a better place to make a hard call.
It is a quieter ambition than “AI will read your scans for you,” and a far more honest one. The plan from here is to push deeper into ultrasound, gather evidence across three countries, and extend the same shape-recognition engine beyond breast imaging into the wider field of oncology.
Imaging volumes keep climbing. Radiologists do not multiply to match them. The pressure to read faster while missing less is not going to ease, which means tools that sharpen the existing human - rather than promising to replace it - are going to age well.
DeepLook is making a specific wager: that the future of cancer detection is not a louder algorithm but a clearer picture, handed to a trained professional at the exact moment of decision. Cleared by the FDA, deployed at name-brand hospitals, and funded to expand - the company has earned the right to keep making it.
Back to that radiologist at 7 a.m., still staring at her snowstorm. She clicks once. The shape she might have missed is now outlined, measured, and impossible to scroll past. A patient she will never meet goes home with an answer months earlier than she otherwise would have. That click is DeepLook Medical. It is a small thing. It is also the entire point.