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Science is too slow. At Edison, we are integrating AI Scientists into the full stack of research, from basic discovery to clinical trials. We want cures for all diseases by mid-century. We have raised a $70M seed to get started. Join us. We need cracked software engineers who want to work on finding cures rather than selling ads and generating slop. If you’re reading this, you’re probably a candidate. We need brilliant AI researchers who want to figure out how AI will accelerate real-world science. We need scientists and researchers with deep expertise in biology, biotech, and pharma who want to figure out how to integrate AI deeply into scientific workflows, from ideation to experimentation, and how to measure success or failure. We need extraordinarily talented generalist operators across BD, sales, product management, and partnerships who can focus on getting our tools into the hands of pharmaceutical companies. If any of these roles sound like you, get in touch. We are also expanding access to our platform. Our goal is to accelerate science writ large. To that end, we will continue to give academics and students 650 credits/mo indefinitely. I can’t promise we’ll keep this up forever, but we will try. Kosmos will still cost 200 credits, and the other agents (Analysis, Literature, etc.) will cost 1 or 2 credits. All paid users will have access to our regular agents, like our Analysis agent, Literature agent, and so on, for free via the UI. API access will still be paid, and users without a paid subscription will continue to get 10 credits per month for those agents. Our $200/mo subscription for 650 credits/mo is staying in place for now, but might be phased out at our next major product update. Along the lines of accelerating science, we’re also doing a major release of PaperQA today, our flagship open source literature agent, as part of our commitment to open science. In the short run, expect major improvements to Kosmos, including the ability to automatically access data, the ability to steer its exploration, and the ability to converse directly with its world model. In the long run, expect exponentially increasing rates of scientific discoveries, in biology and elsewhere. Our round is led by Triatomic Capital, Spark Capital, and a major US institutional biotech investor. We are also joined in this round by existing investors Pillar VC and Susa Ventures, two exceptional early-stage funds who backed us at founding, along with Striker Venture Partners, Hawktail VC, Olive VC, and a host of exceptional angels that includes famous AI researchers, the CEOs of multiple frontier AI labs, and leadership of major biotech and pharma companies.

I’m excited to share PROTON, a pre-trained relational transformer for neurology. 🧠 PROTON generates testable neurological hypotheses, which we evaluated across: 🧬 Parkinson’s disease: genome-wide in vitro and in vivo screens 🧫 Bipolar disorder: patient-derived brain organoids 🏥 Alzheimer’s disease: 610,524 patients tracked across 7 years By pairing AI with real-world experiments, PROTON defines a path for AI-driven discovery in neurological disease. Paper: arxiv.org/abs/2512.13724 Website: protonmodel.ai Code: github.com/mims-harvard/PROT… Model: huggingface.co/mims-harvard/… Learn more below 👇🏽 [1/8]