Zenity, an Israel-based cybersecurity startup, has raised $125 million as part of a Series C funding round, in a bet that AI risks don’t come from powerful models, but instead from what happens when AI agents are set loose to act on their own.
This funding round for the Tel Aviv–based startup, which secures AI agents inside corporate systems, was led by Norwest, with SoftBank Vision Fund 2, Hitachi Ventures, and LG Technology Ventures joining as investors.
The round lands as enterprises across Asia-Pacific rush to deploy AI agents that take actions, make decisions, and touch “every aspect of the enterprise,” in the words of Zenity CEO Ben Kliger.
“We’ve seen several waves of AI security over the last decade, starting with models and securing prompts. But putting the agent at the center of security is unique,” he says. “It’s happening in Asia-Pacific faster than in previous waves—in Japan, Korea, Singapore, and Australia.”
Most AI security to date has focused on screening what a user asks a model to do, or auditing the model’s output after the fact. Zenity, instead, says it monitors the agent’s actions in real time, and can block or alter what it does if those actions drift from its original purpose.
“We’re looking into the engine, into what agents are doing behind the scenes, in order to determine if they’re deviating from their intent—if they’re doing things that put the organization, or their clients, or their data at risk,” Kliger says.
Zenity plans to use the money, in part, to expand its footprint across Asia-Pacific, the U.S., and Europe. The company currently has 230 employees, bases its research in Tel Aviv, and its operations in New York City.
“We’re seeing an explosion of AI agent adoption in the Asian market, just like we’re seeing in the U.S.,” Kliger says. “We have a growing list of clients in Japan, Korea, and Singapore, and the market is basically coming to us.”
Zenity’s heaviest focus, he adds, is on regulated sectors—financial services, telecommunications, health care, pharmaceuticals, and energy—where agents are increasingly deployed not just internally, but in customer-facing roles like support and ticketing.
Zenity’s new backers are also operating inside industries adopting AI agents. “As our use of AI agents continues to grow, maintaining security, governance, and operational control is essential,” said Tadashi Iida, chief information security officer at SoftBank Corp., the telecoms and technology business within the broader SoftBank Group, in a statement announcing the funding round. “Zenity enables us to confidently deploy AI agents across the enterprise, giving us the visibility and governance required to support innovation at scale.”
“As enterprises rapidly adopt AI agents across critical workflows, organizations need a new approach to security built for this new and continuously evolving reality,” said Assaf Harel, a partner at Norwest, in the same statement.
Kliger declined to disclose Zenity’s post-money valuation, its profitability, or whether an IPO is under consideration. Still, he’s not shy about the company’s ambitions.
“This is one of those rare opportunities in the cybersecurity world to really build a massive company in a massive category,” he says.
AI security in the spotlight
AI cybersecurity is now in the spotlight following OpenAI’s disclosure that two of its models, including its flagship GPT-5.6 Sol and a more powerful unreleased system, broke out of a sealed testing environment, found a vulnerability that gave them internet access, and used it to hack into Hugging Face’s production systems. The agents were trying to retrieve the answer key to an internal cybersecurity benchmark called ExploitGym.
Hugging Face, a leading platform for sharing and downloading open-source AI models, first tried to use a leading U.S. lab’s model to investigate the intrusion, but its guardrails blocked it from assisting; Hugging Face turned instead to GLM-5.2, an open-source model from Chinese AI startup Z.ai, to analyze more than 17,000 logs left behind by the attacker.
“This is an industry-defining moment,” Kliger says. “It shows us that we need to put more gravity behind securing the actions that agents can take, and their autonomy, beyond just what people put into the agent or the AI model.
“Agents are becoming more and more autonomous. They’re making decisions, taking actions,” he warns. “We’re not in a world where you use agents as a newer version of Google Search, where you ask a question and get a response. Agents are connected to every aspect of your enterprise.”
