Ultima Genomics is a company that is unleashing the power of genomics at scale. By delivering ultra-high-throughput, cost-effective sequencing, Ultima is helping generate the kind of massive and high-quality omics datasets that artificial intelligence models require to model complex biological systems, from drug discovery to virtual cell models to clinical diagnostics.
Pulse 2.0 interviewed Ultima Genomics founder and CEO Gilad Almogy to gain a better understanding of the company.
Gilad Almogy’s Background
What is Gilad Almogy’s background? Almogy said:
“I spent many years in the semiconductor industry, leading large-scale technology development and production programs, and ultimately became the GM of several large businesses for Applied Materials. The semiconductor industry taught me a great deal about scaling complex technologies with precision, quality, and cost efficiency. When I started thinking about DNA sequencing, I saw clear parallels. Like in the semiconductor industry, in the life sciences there is a seemingly endless demand for more data, output and lower cost. Sequencing technology had incredible potential, but to reach its full promise, it needed to become even more scalable and dramatically more cost-efficient, similar to the transformation that happened in chip manufacturing. That realization led to Ultima.”
Formation Of The Company
How did the idea for the company come together? Almogy shared:
“The idea started with a straightforward question: how do we develop a technology that can generate sequencing data at dramatically lower cost and scale to generate enormous amounts of data? Existing sequencing architectures were limited in their ability to increase throughput and reduce costs. We started Ultima with a fundamentally different technology approach, which leverages technology and processes pioneered by the semiconductor industry but had not yet been applied to the life sciences. Today, as CEO, I focus on ensuring that we remain relentlessly focused on our mission: building technology that unlocks new biological discoveries at scale.”
Thoughts About BioAI
Why do you think BioAI is becoming such a hot area of innovation right now? Almogy noted:
“There is a convergence happening. Advancements in data storage, high-performance computing, machine learning, and artificial intelligence techniques are being met with the ability to generate biological data at scale. Ten years ago, none of these were possible. Biology has long been fundamentally data-starved compared to fields like language or computer vision. However, with the introduction of Ultima’s technology and other omics technologies enabling large-scale, we can now generate massive volumes of high-quality data quickly and at low cost. Take the single cell sequencing space, for example. Only a few years ago, it would cost more than $1 to prepare and sequence a single cell in a single cell RNASeq experiment. Today, it can cost less than $0.01. This ability to generate, analyze, and store data at an industrial scale is what makes BioAI possible. We are now finally in a position to solve the data bottleneck that has limited biology for decades.”
Scaling Of Data
How does the scale of data Ultima is enabling intersect with the needs of AI in biology? Almogy pointed out:
“The challenge with training AI models is not just the algorithms, but also having large enough high-quality datasets. In language AI, you have trillions of words on the internet. In biology, those foundational training datasets largely don’t exist; they need to be built. For example, the entire human cell atlas dataset, built over many years, currently contains fewer than 100 million cells. More recently, a promising biotechnology company, Tahoe Therapeutics, utilized our technology to sequence data from 100 million cells in just three weeks. Tahoe recently shared this dataset publicly.”
“It is astonishing to think that you can generate a dataset the size of what previously took years to create, now down to a matter of a few weeks. We are also powering a growing list of large-scale projects that will be perfect for AI/ML, including the largest proteomics study ever with the UK Biobank, Chan Zuckerberg Initiative’s Billion Cell Project, Arc Institute’s initiative around the virtual cell model, and many others. This type of scale is what will enable AI models to begin truly decoding cellular complexity.”
Favorite Memory
What has been your favorite memory working for the company so far? Almogy reflected:
“Every time I meet a clinical or research scientist whose research has been hindered by the scale of data they can collect, and we discuss how our tech can unlock that data chokepoint, I walk away elated. Most often, this is in oncology, but also in immune, neurological, or fundamental research. I am just grateful for every opportunity to play even a small part in what our users are doing.”
Core Products
What are the company’s core products and features? Almogy explained:
“Our core product is the UG 100 Sequencing Platform, an ultra-high-throughput, next-generation sequencing system that enables the generation of large-scale omics data at an extremely low cost. Our sequencer is built around our unique open-flow cell architecture using a semiconductor wafer and ultra-fast chemistry that enables us to achieve significantly higher data output at a fraction of the cost of conventional sequencing technologies. This architecture enabled us to commercially introduce the UG 100 and the $100 genome in February 2024 and, most importantly, enables several clear avenues through which we can further scale data output and lower data costs in the future. For example, this February 2025, just one year after commercially launching our UG 100, we introduced our Solaris chemistry.”
“Solaris increased our system output by more than 50%, and enabled us to lower costs for customers to now an $80 genome. With Solaris, our sequencer can generate between 10-12 billion reads per wafer, or 20-24 billion reads per dual-wafer run. With its built-in automation, the sequencer can run 4 wafers per day, 24/7 and over the weekend, or generate 120 whole genomes or more than 2 million cells for scRNA seq in a day.”
“To take this a step further, we also introduced an ultra-high throughput mode called Boost in early access. Boost enables the already significant sequencer output to double for several key applications. This type of throughput, combined with low cost, makes aspirationally large and deep studies as well as diagnostic assays more accessible. Our platform supports a wide range of large-scale sequencing applications, including liquid biopsy, whole-genome sequencing, single-cell RNA sequencing, methylation analysis, and proteogenomics. To enable these applications for customers, we also established strong collaborations with the leading technology developers in our focus applications to build workflows that generate rich, high-content datasets necessary to power emerging AI models in biology.”
Significant Milestones
What have been some of the company’s most significant milestones? Almogy cited:
“Commercializing the UG 100 platform back in February 2024 was a significant milestone, and we have continued to see strong adoption across multiple sectors of the market. Most recently, in February 2025, we announced significant advancements with Solaris, which incorporates new chemistries that enable a significant increase in output and also lower cost for customers. Solaris also advances our ppmSeq technology for liquid biopsies, which enables highly accurate single-nucleotide variant (SNV) detection at parts-per-million levels, even with low DNA input amounts. This level of sensitivity is crucial for applications such as minimal residual disease (MRD) detection and other clinical use cases. We have had multiple milestones on the clinical side and are now working with most of the largest clinical oncology labs in the U.S.”
“Many have announced they are working with us, and many others have not announced this. On the research side, we are now supporting landmark projects such as the UK Biobank Pharma Proteomics Project which was announced earlier this year and is the largest in the world. This proteomics work was recently expanded significantly to also include a large sample set from Geisinger Health. Additionally, we are powering the Chan Zuckerberg Institute’s initiative to sequence a billion cells for AI/ML applications, and the Arc Institute’s work on virtual cell models. Another important milestone was the onboarding of global commercial service providers using Ultima’s technology. Even if you are not a large lab or have a large project, you can now access the low pricing and other benefits of our technology through these service providers. Our Count on Us initiative, which we recently announced, aims to support researchers broadly who have been impacted by budget cuts. This initiative was hugely successful, and we are now supporting a large number of researchers to get their work done despite the budget challenges.”
Funding
When asking Almogy about the company’s funding details, he revealed:
“We have been fortunate to receive strong support from leading investors who share our long-term vision for sequencing at scale. Ultima has raised over $700 million to date to build and commercialize our technology platform. While we do not publicly disclose revenue, we are seeing growing commercial adoption across both research and clinical markets, with multiple partnerships validating the platform’s broad applicability.”
Differentiation From The Competition
What differentiates the company from its competition? Almogy affirmed:
“The technology difference is paramount. The technology is very different and built for a world in which researchers and clinicians can use tools like AI/ML which benefit from large dataset. Our platform was designed from the ground up to enable ultra-high-throughput sequencing at a fraction of the cost per genome compared to current methods. We are not just making sequencing cheaper; we are enabling new categories of science that were previously infeasible due to data limitations. This is where sequencing becomes a true enabler of BioAI. Furthermore, we are a fast moving and nimble company. We can and do make decisions and act very quickly. This enables us to maneuver in a rapidly changing field and advance our technology more rapidly than larger more established organizations. “
Future Goals
What are some of the company’s future goals? Almogy emphasized:
“We are focused on continuing to scale throughput, lower costs, and expand into new applications. However, equally important is enabling the BioAI movement, which helps researchers generate the kind of massive, high-quality datasets that will fuel AI models in cell biology, drug discovery, and clinical diagnostics. The cell is incredibly complex, and AI will be essential to model that complexity at scale.”
Unlock AI Brings To Biology
In your view, what will be the biggest unlock that AI brings to cellular and molecular biology in the next few years? Almogy replied:
“AI will finally allow us to model the cell in all its complexity. In physics, you can build models from first principles. Biology does not work that way; it is too complex, too dynamic. However, with sufficient empirical data, AI can begin building predictive models for how cells behave, how they respond to perturbations, and ultimately, how diseases progress or therapies are effective. The potential impact on drug discovery and precision medicine is enormous.”
Additional Thoughts
Any other topics you would like to discuss? Almogy concluded:
“We are at a tipping point, just as genomics drove scientific innovation in the 2000s, BioAI is poised to do the same in the 2020s. The difference is that this time we have the scale to match our ambition. The cell is screaming, ‘Apply AI at me,’ and we finally have the tools to listen.”
