NewCore raises $66M to give AI agents their own identities
AI agents are becoming employees—now they need secure identities.
NewCore, a cybersecurity startup founded by Zohar Alon (ex-Dome9), Amihai Neiderman (ex-Unit 8200), and Erez Yarkoni (ex-CIO of T-Mobile), has emerged from stealth with $66 million in seed funding led by Cyberstarts, with Index Ventures and Evolution Equity Partners participating. The round values NewCore at $300 million. The company addresses a growing challenge: authenticating, governing, and controlling AI agents as they become workplace participants. Companies like Goldman Sachs and McKinsey already treat AI agents as employees, and NewCore argues that traditional identity platforms (like Okta, Microsoft Entra) were designed for humans and will break under the scale of AI agents.
NewCore’s platform manages human and AI-agent identities in a single system, using a split-key architecture that splits credentials between customer and platform to prevent single points of compromise. It also offers an “Agentic Skill” integration package for coding assistants (Claude Code, OpenAI’s Codex, Cursor) so AI tools can access enterprise systems as managed identities. Employees can use a mobile app to grant, review, and revoke agent access, adding human oversight. The startup has fewer than 10 customers and over 10 design partners, plans to start charging this summer, and predicts AI agents may outnumber human employees in tech organizations within a few years.
- NewCore raised $66M in seed funding at a $300M valuation from Cyberstarts, Index Ventures, and Evolution Equity Partners.
- The platform treats AI agents as first-class identities with permissions, life cycles, and revocation, using a split-key architecture for security.
- Integrates with coding assistants like Anthropic's Claude Code and OpenAI's Codex to let AI tools access enterprise systems as managed identities.
Why It Matters
As AI agents become digital employees, NewCore provides a purpose-built identity layer to manage their access securely at scale.