Animals are deeply woven into our society, shaping our lives and the science that supports our health. Yet despite their central role, we still struggle to truly understand animal behavior. We often rely on assumptions, oversimplifications, or incomplete data to interpret how animals move and feel. This gap in understanding limits both our connection to animals and the progress of science critical to improving health.

I realized this firsthand during my PhD in pharmacology while studying the effects of drugs on the brain and animal behavior. Like many behavioral scientists, I spent countless hours scoring animal videos by hand, wrestling with inconsistent tools, and lacking the ability to accurately assess animal behavior.

To solve my own research problems, I began building tools using computer vision and machine learning to analyze behavior automatically, objectively, and in much greater detail. What started as a personal solution grew into BioSyft, a platform designed to help scientists uncover deeper insights from their animal models.

At BioSyft, our mission is to revolutionize how we understand animal behavior and to build stronger connections between species. And in pharmaceutical research, that understanding is more than valuable, it’s urgent. Over 90% of drugs fail in human trials, wasting time, money, and years of effort. For neurological diseases, behavior is one of our greatest tools to study disease and understand if a treatment is works.

By helping researchers listen more deeply to their animal models, we can improve not just the science, but the systems that shape how we treat disease, and how we understand the animals who help us do it.

I invite you to join us, whether you’re a researcher, neuroscientist, or developer, by testing our tools, following our journey on LinkedIn, or simply reaching out to connect.