The evolution of Deep Cognition Labs "DeepCog.ai" is Marvin Minsky's legacy from the MIT Cog project — a tribute to one of the most important debates in AI history and the prophet who was right all along. Read our legacy →

The team building tomorrow's medical AI

We are a specialized AI research company with one mission: build the most accurate, safe, and useful medical LLMs on the planet — and make them accessible to the world.

"Medicine generates more knowledge than any human can absorb. DeepCog.ai exists to make that knowledge computable — to build AI that can read every paper, learn every pathway, and reason through every diagnosis with the rigor of the world's best specialists."

2022
Founded
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Researchers & Engineers
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Published Papers
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Global Offices

The minds behind Deep Cognition Labs

Ron Jagannathan
Ron Jagannathan
CEO & Co-Founder
AI Research Lead and Systems Architect. Physics, Computational Biology. Published 30+ papers on medical NLP and genomic AI.
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Dr. Priya Venkataraman
Chief Science Officer
Expert in LLM alignment and medical safety AI. Former researcher at DeepMind Health. Pioneer of MedDPO preference optimization framework.
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Rahul Sundaresan
CTO
Infrastructure architect for distributed LLM training. Ex-Google Brain. Built training pipelines scaling to 512 H100 GPUs for medical pre-training runs.
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Dr. Lakshmi Nair
Head of Genomics AI
PhD in Computational Genomics from Anna University. Led development of GenomicLLM. Expert in variant interpretation and population genetics AI.
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Dr. Vikram Iyer
Head of Drug Discovery AI
Medicinal chemist turned AI researcher. Former Novartis computational chemistry lead. Built DrugDiscovery-LLM's molecular representation framework.
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Dr. Meena Raghunathan
Clinical AI Advisor
Board-certified physician and AI safety expert. Leads clinical validation of all DeepCog models. Liaison with medical ethics boards and regulatory bodies.

The critical bridge between Biology and Computation

This layer synthesizes fragmented data into a unified understanding of human health, making "incurable" a legacy term. We aren't just building software; we are engineering the future of human longevity.

Building the world's first Biological Intelligence Layer

Our vision is to build the world's first autonomous Biological Intelligence Layer — a future where healthcare doesn't just react to disease but outpaces it.

We are moving beyond static diagnostics into the era of Agentic AI, where a self-evolving ecosystem of Medical and Genomic LLMs works in concert to decode the complexity of human life. By integrating deep genomic insights with real-time physiological data, we create living Digital Twin LLMs — highly personalized, predictive models that simulate outcomes before they happen.

We see a world where AI agents act as tireless partners to clinicians, orchestrating precision care at a cellular level and making "incurable" a legacy term. We aren't just building software; we are engineering the future of human longevity.

The critical bridge between Biology and Computation

This layer synthesizes fragmented data into a unified understanding of human health, making "incurable" a legacy term. We aren't just building software; we are engineering the future of human longevity.

Building sentient healthcare

Our mission is to architect the foundation of sentient healthcare by deploying a unified intelligence network that bridges the gap between raw data and life-saving action. We are dedicated to:

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    Engineering Agentic Systems
    Developing AI agents that proactively manage patient health, navigating complex clinical workflows with the precision of a specialist and the speed of a machine.
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    Decoding Biological Complexity
    Leveraging advanced Medical and Genomic Models to transform trillions of data points into a clear, actionable roadmap for every unique genome.
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    Predicting through Simulation
    Utilizing Digital Twin LLMs to test treatments in a virtual environment first, ensuring that every real-world intervention is optimized for success and safety.
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    Democratizing Elite Medicine
    Scaling the world's most sophisticated medical expertise through Medical LLMs, making high-tier, personalized intelligence accessible to every patient, anywhere.

Our Core Values

These principles guide every model we build, every partnership we form, and every clinical decision our AI helps inform.

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Integrity

We maintain the highest standards of honesty and transparency — in our research, our benchmarks, and our interactions with clinical partners. We never overstate model capabilities or conceal limitations that could affect patient outcomes.

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Innovation

We continuously invest in frontier research to advance specialized medical AI. From novel fine-tuning methodologies like DPO and RLHF to genomic sequence modeling, we push the boundaries of what LLMs can achieve in clinical and biomedical settings.

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Empowerment

We build AI that empowers clinicians, researchers, and healthcare organizations with tools and knowledge to make faster, more informed decisions — without replacing human judgment. The physician remains in control; our models make them more capable.

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Confidentiality

Patient data is sacred. We prioritize the privacy and security of all clinical and genomic data processed through our platform — enforcing HIPAA compliance, SOC 2 Type II standards, and a strict zero-training-on-customer-data policy across every deployment.

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Clinical Partnership

Our customers and clinical partners are at the center of everything we build. We design every model and platform feature through ongoing collaboration with physicians, researchers, and healthcare administrators — ensuring our AI solves real-world clinical problems.

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Responsibility

Medical AI carries unique ethical weight. We hold ourselves accountable for the safety, fairness, and explainability of every model we release — subjecting all outputs to rigorous clinical validation before deployment in any patient-facing or diagnostic workflow.

What drives us

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Medical Accuracy First

We never ship a model without rigorous clinical validation. Every output is calibrated against physician-annotated gold standards. Hallucination in medicine is not a UX problem — it's a patient safety issue.

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Open Science

We publish our research, release models on HuggingFace, and share datasets where possible. Medical AI should advance the entire field, not just our bottom line.

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Global Access

The best medical knowledge should not be limited to the wealthiest institutions. We build lightweight models deployable in low-resource settings across Asia, Africa, and beyond.

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Physician Partnership

AI augments clinicians — it does not replace them. Every model we build is designed as a co-pilot, keeping the physician in the loop and in control of clinical decisions.

Where we work

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Chantilly, Virginia
HEADQUARTERS
15017 Conference Centre Drive
Chantilly, Virginia 20151
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Bethesda, Maryland
RESEARCH OFFICE
6701 Democracy Blvd, Suite 300
Bethesda, MD 20817
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Vancouver, British Columbia
CANADA OFFICE
Vancouver, British Columbia
Canada
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Chennai, India
AI RESEARCH HQ
Olympia National Towers, Guindy Industrial Estate
Chennai — 600032, Tamil Nadu

Home to our core AI research lab, LLM training infrastructure, and 30+ researchers in proximity to IIT Madras and Anna University.
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Pune, India
ENGINEERING CENTER
Rajiv Gandhi Infotech Park, Hinjewadi
Pune — 411057, Maharashtra

Platform engineering, MLOps infrastructure, and enterprise partnerships. Close to India's leading pharma and biotech ecosystem.
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San Francisco, USA
NORTH AMERICA OFFICE
South of Market (SoMa) District
San Francisco, CA 94103

Business development, US healthcare partnerships, and regulatory affairs for FDA AI/ML medical device guidance.
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Singapore
ASIA-PACIFIC HUB
One-North Business Park
Singapore 138522

APAC partnerships, clinical trial AI for Southeast Asian markets, and collaboration with A*STAR biomedical research.

A Tribute to Marvin Minsky & the Cog Project

DeepCog.ai draws its name and its philosophy directly from one of the most important debates in the history of artificial intelligence.

"Robotics research is really a software problem."

Marvin Minsky, Turing Award laureate & co-founder of MIT's AI Laboratory, on the Cog Project

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MIT's Cog Project (1993–2003)

The Humanoid Robotics Group at MIT launched Cog — a humanoid robot built on the hypothesis that human-level intelligence requires embodied social experience. Cog could see, hear, track faces, and respond to human interaction. Despite a decade of pioneering engineering, development ceased in 2003. Today Cog is retired to the MIT Museum.

Wikipedia: Cog (project) →  ·  MIT CSAIL: Cog →

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Marvin Minsky's Dissent (1927–2016)

Marvin Minsky — co-founder of MIT's AI Laboratory, Turing Award laureate (1969), and one of the acknowledged fathers of artificial intelligence — criticized Cog directly. He argued it should be built as a software simulation, because intelligence is fundamentally a computational problem, not a mechanical one.

His landmark works — The Society of Mind and The Emotion Machine — all converged on the same thesis: minds are made of ideas, not metal.

Wikipedia: Marvin Minsky →

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DeepCog.ai — Minsky's Vision, Finally Realized in Software

The name DeepCog is a deliberate homage. Where Cog reached for cognition through mechanical arms and camera eyes, DeepCog reaches for it through language, medical reasoning, and knowledge encoded in billions of parameters. Where Cog aimed to learn by interacting with humans in a lab, DeepCog learns from 42 million peer-reviewed papers, clinical trial records, genomic databases, and expert medical reasoning chains.

After successive attempts at embodied robotic intelligence failed to achieve human-level cognition, the field turned to exactly what Minsky had prescribed — software simulation at scale. The transformer architecture, large language models, and domain-specific pre-training vindicated his position completely. DeepCog.ai was born from that arc.

The vision is the same as Cog's. The medium is software — exactly as Minsky said it should be.