Participated · Equity · Aug 2026

Network Bio focuses on linking fragmented biorepositories at major academic medical centers to provide trusted, permissioned access to biological samples (blood, tissue), genomic information, and longitudinal clinical data. The company’s work centers on interoperability, standardization, consent management, governance, and privacy-preserving computation to make these assets usable for research, drug discovery, diagnostics, and AI development. Its stated plans include creating federated biological data networks and consent and identity infrastructure that hospitals will trust. Financially, the company recently raised $50 million to advance this infrastructure; the article does not detail other financial metrics, revenue, users, or prior funding rounds. The effort is framed as building an important healthcare AI infrastructure layer by enabling access to high-quality biological samples connected to clinical outcomes.

Participated · Series B · Apr 2026

Beacon Biosignals develops FDA-cleared wearable EEG technology combined with advanced AI to capture and analyze real-world neural data. Its platform provides clinicians and biopharma partners with objective measures of brain function intended to accelerate research, improve diagnostics and guide new treatments across neurology, psychiatry and sleep medicine. The company is led by CEO Jacob Donoghue and is based in Boston, MA. Beacon reported cumulative funding of over $132M following the Series B extension. The company plans to use the new proceeds to further scale at-home EEG deployments and expand its analytics capabilities to support diagnostics, clinical trials and precision medicine.

Participated · Series A · Mar 2026

RunSybil builds an AI agent called Sybil that continuously probes live applications to find, exploit and document real security vulnerabilities without humans in the loop. Its approach focuses on testing running systems—exploring, chaining vulnerabilities and testing authentication boundaries—rather than analyzing source code pre-deployment. The company was co-founded in 2023 by Ari Herbert-Voss, who previously led security research at OpenAI, and Vlad Ionescu, who led offensive security red teams at Meta. RunSybil reports working with startups (including Cursor, Turbopuffer, Notion, Baseten and Thinking Machines Lab) as well as several major financial institutions and Fortune 500 customers. Customers have reported that Sybil discovered critical vulnerabilities missed by traditional penetration tests and red teams. Investors and founders position the product as particularly relevant for regulated industries facing strict audit and compliance requirements as AI-driven development accelerates.

Participated · Seed · Mar 2026

Autoscience operates a virtual AI laboratory composed of automated scientists and automated engineers that ideate, validate, and deploy new machine learning models. The company targets high-stakes applications including financial services, manufacturing, and fraud detection and offers a managed service that continuously delivers model improvements. Autoscience is based in San Mateo, California, and its team includes researchers from Google X, MIT, and Harvard. The company has achieved milestones including a peer-reviewed paper at an ICLR 2025 workshop and a Silver Medal in the Kaggle Santa 2025 competition. With $14 million in seed funding, Autoscience plans to scale its deployments for Fortune 500 and large private customers and grow its engineering team.

Participated · Seed · Jan 2026

Humans& is a newly launched AI lab building collaboration-focused artificial intelligence designed to keep human insight at the center of work. Its product vision is an orchestrator that serves as the “connective tissue” between people and AI, coordinating workflows rather than replacing human actors. The company aims to set a new standard for how AI supports human connection by developing tools that enable smoother, more intuitive cooperation across teams and intelligent systems. The founding team includes researchers and engineers with backgrounds at OpenAI, Anthropic, Google DeepMind, Meta, and xAI; CEO Eric Zelikman previously contributed to the Grok models at xAI and authored the STaR paper at Stanford. Humans& has not disclosed revenue or user metrics, but it enters the market with significant capital resources. The company raised a $480 million seed round that values it at $4.48 billion, giving it one of the largest war chests ever for an AI seed-stage startup. This sizeable funding positions Humans& to aggressively hire, scale infrastructure, and accelerate product development.