Enterprise AI adoption has hit a governance wall. 93% of executives report challenges implementing AI governance and security guardrails, according to new research, creating a trust crisis that’s blocking the transition from pilot programs to production systems at scale.

JetStream, founded by CrowdStrike’s former Chief Product Officer Raj Rajamani and other cybersecurity veterans, has raised $34 million in seed funding to tackle what the company calls “the trust problem with AI.” The Redpoint Ventures-led round includes backing from CrowdStrike CEO George Kurtz, Wiz CEO Assaf Rappaport, and Okta co-founder Frederic Kerrest.

Dyna.Ai closed an eight-figure Series A round led by Lion X Ventures, targeting the enterprise AI pilot-to-production gap as Southeast Asia’s AI market heads toward $16 billion by 2033.

The Singapore-based startup announced the multimillion-dollar funding on March 1, with participation from OCBC Bank’s Mezzanine Capital Unit, Taiwan-listed ADATA, a Korean financial institution, and finance industry veterans. While the exact amount remains undisclosed, the company confirmed the round falls within the eight-figure range ($10-99 million USD).

t54 Labs raised $5 million in seed funding to build trust infrastructure for AI agents that can autonomously initiate payments and execute financial transactions—addressing what founder Chandler Fang calls the complete absence of standardized identity verification, risk assessment, and accountability systems for autonomous agents operating in financial markets.

As AI agents gain the ability to move real money without human oversight, the infrastructure gap around trust, compliance, and accountability has become a critical bottleneck preventing enterprise adoption. Unlike human users who can be verified through traditional KYC processes, autonomous agents lack established frameworks for identity confirmation, risk scoring, or liability assignment when transactions go wrong. This creates an enterprise deployment crisis where agents powerful enough to automate complex financial workflows remain too risky for production use.