Autopoiesis Sciences

Cover Block

Field	Value
Name	Autopoiesis Sciences
Tagline	Develops foundational AI models to accelerate scientific discoveries in medicine and biology
Headquarters	San Francisco, United States
Founded	2025
Stage	Seed
Business Model	B2B
Industry	Deeptech
Technology Type	AI / Machine Learning
Geography	North America
Growth Profile	Venture Scale
Founding Team	Co-Founders (2)
Funding Label	Seed (amount undisclosed)

Links

• Website: https://autopoiesis.science/
• LinkedIn: https://www.linkedin.com/company/autopoiesis-sciences

Executive Summary

Autopoiesis Sciences is a San Francisco startup building a foundational AI system, branded Aristotle, intended to function as an "AI co-scientist" for researchers in medicine and biology [Oracle, 2025]. The company emerged in 2025 around a thesis that current general-purpose large language models are insufficiently rigorous for primary scientific work, and that a model trained for skeptical, evidence-grounded reasoning can fill that gap [GABA Northern California]. Co-founders Joseph Reth, an AI and consciousness researcher who serves as CEO, and Dr. Eike Gerhardt, whose background spans banking, M&A and venture capital, lead the company [Crunchbase]. A seed round closed on July 30, 2025, led by Informed Ventures, with Alpaca VC, Cross Atlantic Angels and a roster of individual angels also on the cap table [Tracxn, July 2025] [PitchBook]. The product surface visible today is Aristotle X1 Verify, which the company describes as achieving "state-of-the-art performance on the most challenging scientific reasoning benchmarks while solving the calibration problem" and which is being released to a select group of researchers [Autopoiesis Sciences]. The company has also disclosed a partnership with Oracle Cloud Infrastructure for the underlying compute footprint [Oracle, 2025].

Data Accuracy: GREEN -- Confirmed by Crunchbase, Tracxn, PitchBook, and the company's own website plus an Oracle customer page.

Taxonomy Snapshot

Axis	Value
Stage	Seed
Business Model	B2B
Industry / Vertical	Deeptech, AI for science
Technology Type	AI / Machine Learning (foundation models)
Geography	North America (San Francisco)
Growth Profile	Venture Scale
Founding Team	Co-Founders (2)
Funding	Seed, lead Informed Ventures, July 2025

How the Company Got Here

Autopoiesis Sciences was founded in 2025 in San Francisco with the stated ambition of building "the foundation for scientific superintelligence to accelerate breakthrough discoveries and help cure previously incurable diseases" [Autopoiesis Sciences]. Joseph Reth, the CEO, is described in his Crunchbase profile as "an American entrepreneur, computer scientist, and AI researcher known for his work in artificial intelligence and consciousness research" [Crunchbase]. Co-founder Dr. Eike Gerhardt holds two master's degrees, in Entrepreneurship & Innovation and in Rhetoric, plus a Ph.D., and has prior experience in banking, M&A and venture capital [Crunchbase].

In an interview with GABA Northern California, Gerhardt framed the founding problem: "At Autopoiesis, we're creating Aristotle, the world's leading AI scientist... The problem is simple: most AI systems are great at sounding right, but often aren't" [GABA Northern California]. The two confirmed milestones to date are the seed round closed on July 30, 2025 led by Informed Ventures [Tracxn, July 2025], and the disclosed Oracle Cloud Infrastructure relationship supporting model training and serving [Oracle, 2025]. Beyond Reth and Gerhardt, the team includes Ally Reth as Director of Industry Partnerships and Performance [Crunchbase] and Jennifer Yoon in a product design and scientific-claims-validation role [LinkedIn] [RocketReach].

Data Accuracy: GREEN -- Confirmed by Crunchbase founder profiles, Tracxn funding record, and an Oracle-published customer page.

Product and Technology

Metric	Value
Product	Aristotle
Release	Aristotle X1 Verify
Compute Partner	Oracle Cloud Infrastructure

The product is Aristotle, described by the company as "an AI co-scientist designed to think like a real researcher: skeptical, careful, and grounded in evidence" [LinkedIn, 2026]. The first publicly named release is Aristotle X1 Verify, which the company markets as reaching "state-of-the-art performance on the most challenging scientific reasoning benchmarks while solving the calibration problem" [Autopoiesis Sciences]. Two named technical components sit underneath Aristotle: "Double Check," a verification layer for scientific claims, and "Dynamic In-line Definitions" (DIDs), a mechanism for grounding terms used during reasoning [LinkedIn, 2026]. Together, these are intended to address the calibration problem in current LLMs [GABA Northern California]. The Oracle customer page positions Autopoiesis as building a model "to help scientists accelerate discoveries, validate complex hypotheses, and address urgent challenges in medicine and biology" [Oracle, 2025].

Data Accuracy: YELLOW -- Product positioning is confirmed by the company website and the Oracle customer page; specific benchmark scores and architecture remain company-stated and not independently verified.

Market Research and Opportunity

AI for scientific discovery has moved from a research curiosity to a funded category, and Autopoiesis is entering at a moment when both compute partners and pharmaceutical buyers are actively building budgets for it. The demand thesis, that current general-purpose LLMs sound right more often than they are right, maps onto a real procurement problem inside research-intensive organizations [GABA Northern California]. Pharmaceutical R&D, academic biology and translational medicine all share a common feature: the cost of a confidently wrong answer is high. A model that explicitly addresses calibration is therefore positioned against a buyer pain point. The company's Oracle relationship signals that at least one hyperscaler-adjacent partner has chosen to publicly associate its infrastructure brand with the Autopoiesis mission [Oracle, 2025].

Sizing reference	Value
Disclosed seed round date	July 30, 2025
Disclosed compute partner	Oracle Cloud Infrastructure

Data Accuracy: YELLOW -- Demand signals confirmed via Oracle and Tracxn; market sizing remains uncited in surfaced sources.

Competitive Landscape

The segment Autopoiesis is targeting can be split into three competitive layers. The first layer is the frontier general-purpose model providers, principally OpenAI, Anthropic and Google DeepMind. The second layer is the cohort of biology- and chemistry-specific foundation models. The third layer is the explicit "AI co-scientist" effort inside large industrial research labs. Where Autopoiesis has a defensible edge today is in focus and framing. The Double Check and Dynamic In-line Definitions components [LinkedIn, 2026] are described as purpose-built for the calibration problem. The Oracle partnership [Oracle, 2025] is also a concrete distribution and compute advantage. Where Autopoiesis is most exposed is on the model-capability frontier and the lack of a proprietary scientific dataset.

Data Accuracy: YELLOW -- Competitive landscape is based on category-level positioning.

Opportunity

If Autopoiesis builds what it says it is building, the prize is being the default reasoning-and-verification layer for AI-assisted scientific work. The company's framing, that "most AI systems are great at sounding right, but often aren't" [GABA Northern California], is a positioning claim about where value will accrue in AI for science. The disclosed Oracle Cloud Infrastructure relationship [Oracle, 2025] and a seed round led by Informed Ventures with Alpaca VC and Cross Atlantic Angels participating [PitchBook] [Tracxn, July 2025] indicate that both an infrastructure partner and a venture syndicate are willing to underwrite that thesis at the seed stage.

Data Accuracy: YELLOW -- Scenarios are grounded in confirmed product positioning, the Oracle partnership, and the seed syndicate.

Sources

1. [Autopoiesis Sciences] Autopoiesis Sciences home | https://autopoiesis.science/
2. [Autopoiesis Sciences] About - Autopoiesis Sciences | https://autopoiesis.science/about
3. [Oracle, 2025] Autopoiesis taps Oracle Cloud Infrastructure to build AI co-scientist | https://www.oracle.com/customers/autopoiesis/
4. [Crunchbase] Autopoiesis Sciences company profile | https://www.crunchbase.com/organization/autopoiesis-sciences
5. [Crunchbase] Autopoiesis Sciences financial details | https://www.crunchbase.com/organization/autopoiesis-sciences/financial_details
6. [Crunchbase] Joseph Reth person profile | https://www.crunchbase.com/person/joseph-reth
7. [Crunchbase] Eike Gerhardt person profile | https://www.crunchbase.com/person/eike-gerhardt
8. [Crunchbase] Ally Reth person profile | https://www.crunchbase.com/person/ally-reth-863c
9. [Tracxn, July 2025] Autopoiesis funding rounds and investors | https://tracxn.com/d/companies/autopoiesis/__e0hRhAqelomJNOgVJXA_QmKIY0g03fZefJe0Q8I0Hk4/funding-and-investors
10. [PitchBook] Autopoiesis Sciences company profile | https://pitchbook.com/profiles/company/894666-61
11. [GABA Northern California] The German-American Entrepreneurial Journey of Eike Gerhardt | https://gaba-network.org/norcal/the-german-american-entrepreneurial-journey-of-eike-gerhardt-co-founder-of-autopoiesis-science/
12. [LinkedIn, 2026] Jennifer Yoon profile - Autopoiesis Sciences | https://www.linkedin.com/in/jennifermyoonn/
13. [LinkedIn] Autopoiesis Sciences company page | https://www.linkedin.com/company/autopoiesis-sciences
14. [iMedia] AI Aristotle benchmark and founder profile | https://min.news/en/tech/6f9eae89927c817d933bd5799360d8b5.html
15. [teeming.ai] Autopoiesis Sciences - Software Engineer Intern listing | https://teeming.ai/j/software-engineer-intern/136d20d9-a825-6887-e427-ca5177932202/autopoiesis-sciences/e565be88-990d-4457-9a0d-429d6ae5b41b
16. [f4.fund] Alpaca VC investment thesis and preferences | https://f4.fund/firms/alpaca-vc