Sanjay Sabnani is an author and independent researcher in Causal Neuro-Symbolic AI. He serves as a senior executive and board member at a private-equity-owned technology company, where he leads legal, compliance, governance, and AI research and development. He is the author of ActualizationOS and the creator of the Causal Wisdom Harvester, a patent-pending system for producing structured causal models from domain texts. Earlier in his career he founded and took public CrowdGather, Inc., a digital media network that reached millions of monthly users.
Sanjay Sabnani works across two fields that rarely overlap: corporate leadership and the study of the mind. He is a senior executive and board member at a private-equity-owned technology company, where he leads legal, compliance, governance, and AI research and development, and an independent researcher and author whose work centers on causal structure — in markets, in organizations, in philosophical texts, and in human cognition.
His earlier career includes founding and taking public CrowdGather, Inc., a digital media network that reached millions of monthly users. He holds two U.S. patents and co-authored a chapter in a Wiley medical textbook.
A decade of investigation into the mind’s operating system produced ActualizationOS, his first book. The Zero-Axis Theory and Mūla-Śūnya-Kārikā emerged from the same work as independent philosophical contributions.
His AI research developed from the same methodology. The causal-extraction process he built for contemplative texts proved to work on any unstructured corpus — maritime law, patent law, medical literature — and became the Causal Wisdom Harvester, a patent-pending system that produces structured causal models from domain texts.
He welcomes collaboration in Causal Neuro-Symbolic AI with others working at the intersection of causal reasoning, knowledge representation, and the alignment of AI with human judgment.
264 pages. A diagnostic system for inner change — grounded in neuroscience and contemplative traditions, built from a decade of lived investigation. The first personal transformation book that ships with working software.
The Causal Wisdom Harvester is a patent-pending system that produces Structured Causal Models (SCMs) from domain texts — enabling AI systems to apply structured, traceable reasoning in constrained domains.
Applied to a single regulatory document (the International Regulations for Preventing Collisions at Sea), the system produced a complete queryable causal graph. The same approach has been applied to US patent law, medical literature, and contract corpora.
A variant processes interview and behavioral data into Structured Psychographic Models (SPMs) — encoding a person’s decision architecture as a reasoning layer an AI can operate from. The “Sanjay” AI twin on this site is a working demonstration.
The extraction methodology is proprietary and patent-pending. The AI demos on this site use models produced by the system but do not expose the underlying architecture. Research collaboration and domain inquiries welcome.
From a single regulatory document (COLREGs)
Two modes. Both are working demonstrations of the Causal Wisdom Harvester.
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The Identity Immune System. Why founders sabotage their next stage because their nervous system prefers familiar stress. The ROI of getting out of your own way.
Why affirmations backfire, why dropping the desire is what fulfills it, and the physics of how inner change actually works when you stop forcing it.
Extracting causal graphs from text. Why LLMs mirror the recursive-reification loop of consciousness. The Digital Agency Corporation framework for AI in the economy.
How the “Second Arrow” works. The State-Method Rule — why the right practice in the wrong state turns medicine into poison. The Third Wish.
I’m looking for collaborators, podcast hosts, and anyone working where causal AI meets the structure underneath things.