In 2020, we sat down with medicinal chemists at leading pharmaceutical companies and research institutions. What we discovered shocked us.
These brilliant scientists—people pushing the boundaries of drug discovery—were spending hours every day performing mundane tasks. Manually searching through multiple disconnected databases. Planning synthetic routes on paper. Re-entering the same compound data into five different systems. Losing decades of research because handwritten lab notebooks couldn't be digitized or searched.
We watched a senior chemist spend 40 minutes trying to find a compound her team had synthesized two years ago. The structure was buried in a scanned notebook, invisible to digital search. That experiment—and the knowledge it contained—was effectively lost.
The Problem Was Bigger Than We Thought
The pharmaceutical industry sits on 50+ years of invaluable R&D data: failed experiments that revealed key SAR insights, handwritten notebooks documenting synthetic routes, chemical structures trapped in PDF documents and patent drawings. But this knowledge is trapped, disconnected, and unsearchable.
Meanwhile, the tools available to scientists were fragmented point solutions. One system for molecular search. A separate tool for retrosynthesis. Another platform for docking. A different system for lab notebooks. Each requiring manual data re-entry. Each creating its own data silo.
The result? Wasted time. Lost knowledge. Duplicated efforts. Slower drug discovery. And ultimately, delayed treatments for patients who need them.
The Breakthrough
We knew there had to be a better way. Our founding team—AI researchers, pharmaceutical scientists, and software engineers—set out to solve the hardest problem first: digitizing handwritten chemical structures.
After months of research and thousands of experiments, we achieved what no other company had: 93.2% accuracy on handwritten chemical structure recognition. For the first time in history, decades of handwritten lab notebooks could be unlocked and made searchable.
But we didn't stop there. We realized that solving one part of the workflow wasn't enough. Scientists needed a truly unified platform—one that seamlessly integrated every step of drug discovery from molecular search to synthesis planning to lab documentation.
Building the Unified Platform
Today, OCSR.ai is the only platform that brings together molecular search (1.3 trillion molecules), AI-powered molecular generation, intelligent retrosynthesis, protein structure prediction, molecular docking, virtual screening, document digitization, and electronic lab notebooks into one cohesive ecosystem.
Every product shares data automatically. Search for a compound in CIE, and it's instantly available in Janak for generation, Rasayan for synthesis planning, ProteinLab for docking, and ELN.bio for documentation—with zero manual re-entry. Your private compound registry grows organically as you work, creating a single source of truth for all your research data.
What Drives Us
We believe that every hour saved in the lab is an hour gained for patients. Every piece of lost knowledge recovered is a potential breakthrough rediscovered. Every data silo eliminated is a barrier removed from the path to new treatments.
The scientists we work with are trying to cure cancer, develop treatments for rare diseases, and solve humanity's most pressing health challenges. They deserve tools that match their ambition—tools that augment their expertise rather than slow them down.
That's why we built OCSR.ai. Not just to be another software vendor, but to be a true partner in accelerating scientific discovery. To unlock the knowledge trapped in decades of research. To give scientists more time for what they do best: science.
Join Us
We're just getting started. Every day, leading pharmaceutical companies and research institutions join the OCSR.ai platform, contributing to a growing ecosystem of shared knowledge and accelerated discovery.
Whether you're a medicinal chemist frustrated by disconnected tools, a research director looking to unlock your organization's historical data, or a scientist who believes there's a better way to do drug discovery—we'd love to work with you.
Together, we can transform how scientific discovery happens. Together, we can accelerate the path from molecule to medicine.