Intactis Bio (Salt Lake City) pioneers bio-computation using living neural tissue, enabling energy-efficient AI/ML. The platform integrates neurons with silicon, reduces costs and footprint. The company recently received $100K, part of a $300K commitment from RPV (San Francisco).
Salt Lake City, Utah — September 26, 2025
In the heart of Salt Lake City, a quiet revolution in computing is underway. Intactis Bio, a startup incubated at Altitude Labs (Salt Lake City), is developing the world’s first engineered biological computers powered by 3D printed, living neural tissue, aiming to tackle one of the most pressing challenges in modern AI: energy consumption.
Headed by Daniel Rodriguez-Granrose, the company combines deep expertise in neuroscience, tissue engineering, and artificial intelligence to build what they call “bio-computation” platforms—living neural networks capable of performing AI/ML tasks with unprecedented efficiency.
TechBuzz met Daniel Rodriguez-Granrose at the Inception Sunset Barbeque in Deer Valley and sat down with him again this week to find out about how the company is doing, take a look at its technology, and learn about interest from investors. One specialized investor, RPV (San Francisco)—an early-stage, deep-tech, neuroscience-focused fund founded in 2021—recently provided Intactis Bio with an initial $100,000 pre-seed investment. It has committed an additional $200,000 toward an eventual $2.5 million seed round, which is still open.
Beyond traditional venture support, Intactis has received grants from Altitude Labs, The Utah State Government, and a network of defensive accelerationist organizations—including Nodes, SingularityNET, DeepFunding.ai, and the Edge Esmeralda community—which aim to advance science and technology responsibly. These grants support the development of Intactis’s bio-computation platform while emphasizing safe, energy-efficient AI deployment.
The Bio-Computing Challenge
Modern AI workloads are voracious energy consumers. Large language models and other deep learning architectures require massive parallel processing, consuming electricity at a scale that is increasingly unsustainable. Data centers strain local energy grids and exacerbate environmental concerns such as water scarcity—particularly in Utah, where local data center operations impact the shrinking Great Salt Lake.
“The combination of having scaled neural cultures in large bioreactors and seeing the modern AI energy crisis made it clear,” Daniel Rodriguez-Granrose explains, “if we could build AI on a neural tissue substrate instead of silicon chips, we would not only gain computational efficiency but also dramatically reduce environmental impact.”
To put it in perspective, a human brain performs roughly 10,000 times more operations per second than a supercomputer while consuming 1 million times less energy per day. Intactis Bio aims to harness these principles at scale, effectively offering AI computation without the energy limitations inherent to traditional silicon-based systems.
How It Works: From Stem Cells to Biochips
At the core of Intactis Bio’s approach is the engineering of living neural tissue. The process begins with pluripotent stem cells, derived from human blood samples, which are converted into neurons. These neurons are then 3D-printed and vascularized, forming robust, three-dimensional structures capable of sustained life. Each substrate contains tens of millions of neurons—roughly the size of a grade-school eraser but 600,000 times larger than any comparable engineered neural tissue previously demonstrated.
Once the tissue is alive, it interfaces with custom brain-machine bioreactors and electrode arrays capable of both stimulating and recording neural activity. These electrodes deliver electrical and biochemical signals to the neurons, encoding computational tasks and reinforcing learned behaviors. The tissue itself then processes inputs, executes calculations, and generates outputs—essentially acting as a living processor.
What’s unique about our system is that it’s not just an artificial simulation of neurons,” Rodriguez-Granrose explains. “The tissue itself can perform calculations. In a recent experiment the neurons actually controlled their own environment—by deciding when to pulse their bioreactor with nutrients over 21 days, functioning simultaneously as a sensor, a controller, and a computational engine.
This proof-of-concept study, which has been patented in multiple countries, demonstrates the practical viability of neural tissue as a computation substrate and sets the stage for commercial applications. While not yet peer-reviewed in academic journals, the research has been robust enough to attract investor interest and validate the approach from a commercial perspective.
The Biotransformer: Generalized Bio-Computation
To make biological computation accessible to AI/ML developers without requiring deep neuroscience expertise, Intactis has developed the Biotransformer, a proprietary AI/ML architecture that functions as a plug-and-play interface between living neurons and conventional silicon systems. The platform integrates with PyTorch and supports standard AI workflows, allowing developers to train models with biological intelligence much like they would with GPUs.
The Biotransformer supports multiple industry verticals, including:
By encoding data into electrical patterns, delivering them to neural tissues, and reinforcing learned behavior through biochemical cues, Intactis Bio creates hybrid “bio-artificial neural networks” that can perform complex computations previously unachievable with traditional hardware.
The Team Behind the Breakthrough
Intactis Bio’s progress reflects a convergence of expertise spanning neuroscience, tissue engineering, AI, and commercialization. The leadership team includes:
This seasoned team blends foundational science with applied technology, forming a rare convergence of AI, neural tissue engineering, and commercialization expertise in one company.
Business Model and Market Approach
Intactis Bio’s business model is equally ambitious. The company plans to co-locate bio-computation data centers alongside energy-constrained silicon-based facilities, providing AI/ML computation services with significantly reduced energy consumption.
Their projections suggest:
Initially, Intactis will train models on silicon hardware and expand to inference on living neural biochips. This hybrid approach enables customers to leverage biological intelligence without requiring them to understand the underlying neuroscience.
Recently, the company launched its phase 1 Biocomputation Alpha platform encompassing both free and paid tiers, with paid users prioritized for capacity and co-development. Phase 2 is planned for 2027. By combining silicon and biological processing, the system promises a “biological superintelligence” inside every data center, enabling massive parallel processing with energy efficiency impossible for conventional hardware.
Scientific and Commercial Traction
Intactis Bio has demonstrated significant scientific traction, including:
The company has also conducted customer interviews and NSF I-Corps programs to validate industry segments and use cases, ensuring that bio-computation is aligned with market demand.
The company has filed patents in 7+ countries, protecting both tissue engineering methods and the company's proprietary Biotransformer AI/ML architecture.
Looking Ahead: Exaflop Biohybrid Machines
Intactis Bio’s long-term vision is the development of exaflop-scale biohybrid machines, integrating biological reasoning into AI workflows at data center scale. Unlike traditional AI, which only reinterprets existing datasets, these systems could generate new insights and adapt in real time, offering a form of intelligence closer to human reasoning while remaining far more energy-efficient.
“We aim to scale bio-computation alongside silicon processors in real-time, expanding computation without the constraints of electricity or data center footprint,” Rodriguez-Granrose explains. “By leveraging neurons’ extreme efficiency, we can deliver AI/ML that’s both powerful and sustainable.”
Converging Science, Technology, and Responsibility
Intactis Bio’s work exists at the convergence of several rapidly advancing fields: neuroscience, AI, tissue engineering, and ethical technology development. By collaborating with organizations such as Nodes, SingularityNET, DeepFunding.ai, and Edge Esmeralda, the company ensures that its innovations in bio-computation are not only powerful but also developed responsibly. These groups, guided by the principles of defensive accelerationism, aim to advance scientific breakthroughs while mitigating risks associated with powerful AI systems.
As AI continues to scale globally, the need for energy-efficient, responsible computation becomes increasingly urgent. With its living neural biochips, hybrid AI architecture, and multidisciplinary team, Intactis Bio may be positioning itself at the forefront of a new era in computation—one where biological intelligence meets artificial intelligence in practical, scalable, and environmentally conscious ways.
Daniel Rodriguez-Granrose will be presenting at the Mormon Transhumanist Association (MTA) monthly meeting on Sunday, November 9th, at 8 p.m. The MTA is dedicated to promoting the ethical use of science and technology to enhance human potential in ways consistent with Mormon theology. Our mission is to become compassionate creators, working collaboratively to improve the human condition.
He will also be a keynote speaker at Superintelligence Summit, Nov 17, 2025 in Buenos Aires.
To learn more about the phase 1 alpha or for other inquiries, contact Daniel Rodriguez-Granrose at daniel@intactis.bio.