Twin1 AI has emerged from stealth with $20 million in seed funding to develop AI-powered digital twins designed for professional knowledge workers, with the round co-led by Bessemer Venture Partners, Tribeca Venture Partners, and Aramco Ventures. Founded in 2025 by Dr. Lewis Z. Liu, Tom Cahn, Huiting Liu, and Dr. Jonathan Budd, the company is building technology that aims to preserve and extend employees’ knowledge, judgment, relationships, and working context across organizations. Twin1 plans to use the funding to expand its teams in San Mateo and London, strengthen go-to-market operations, and continue developing its enterprise AI infrastructure.
Building Digital Twins for Professionals
Twin1’s platform creates an individual digital twin for each professional, using context from workplace information such as emails, meetings, documents, and internal systems to provide responses and support actions on the user’s behalf. The technology operates across commonly used tools including Slack, Microsoft Teams, Outlook, Gmail, Google Drive, and SharePoint, allowing digital twins to work within existing enterprise environments rather than requiring employees to move into a separate system. The company describes its wider Twin Network as a coordination layer through which digital twins can locate relevant expertise, exchange permissioned knowledge, and support collaboration between employees and AI agents.
Privacy and Enterprise Governance
Privacy and governance are central to Twin1’s positioning, particularly as companies look to deploy generative AI across sensitive internal data and regulated business environments. Users maintain control over what information their digital twins can access and share, while enterprise policies, inherited permissions, AI-based safeguards, and human approvals determine how information moves between people and systems. Twin1 also provides an enterprise MCP server that enables other AI agents and business tools to access governed context from individual twins or the wider network, while supporting SaaS, single-tenant, and private-cloud deployment options.
Early Enterprise Adoption
The company says its platform has already been deployed for more than a year with organizations across legal services, financial services, and energy, giving Twin1 an early base of enterprise customers before its public launch. Customers named by the company include Linklaters, Orrick, Dechert, Customers Bank, and Aegis Energy, with users reportedly automating between 30% and 50% of communications-related work performed by knowledge workers. Twin1 is particularly targeting large organizations where institutional knowledge is fragmented across teams and software systems and where confidentiality, access controls, and governance can limit the use of more generalized AI tools.
Broad Investor Support
In addition to the three co-lead investors, the seed round attracted backing from EJF Ventures, Tin Alley Ventures, AGI House Ventures, Neo, F-Prime, Btech Consortium, Antiportfolio Ventures, Lakestar, Notion Capital, Insiders, and strategic investor Orrick. Angel participants included Dawn Capital co-founder Haakon Overli, Wiz co-founder Roy Reznick, Notable Capital Managing Partner Hans Tung, former McKinsey Senior Partner Kevin Buehler, climate technology investor Robert Trezona, and former Macquarie Capital global co-head Dan Wong. Several investors had also supported Eigen Technologies, the founders’ previous venture, extending their backing to the team’s latest enterprise AI company.
Twin1 AI is entering the enterprise AI market with a model centered on giving professionals digital counterparts that can extend their expertise while maintaining individual control over sensitive knowledge and organizational context. Rather than consolidating employee information into a single generic AI layer, the company is betting that enterprises will favor systems where context remains tied to specific people, permissions, and governance rules. With $20 million in new funding and initial deployments across several regulated industries, Twin1 will now focus on expanding commercial adoption and developing its technology as enterprises seek more controlled ways to integrate AI into everyday knowledge work.