Artificial Intelligence

Catch Raises $5 Million for AI Executive Assistant With Guardrails

Catch promises the capabilities of a trusted executive assistant, with built-in controls governing what data and systems it can access.

Catch promises the capabilities of a trusted executive assistant, with built-in controls governing what data and systems it can access.

Catch, an agentic admin assistant for leaders, has raised $5 million to accelerate its purpose to solve executives’ daily pain points.

The funding was co-led by Entrée Capital and Pitango, with participation from Seedcamp and Factorial Capital.

Catch, an AI startup co-founded by Nir Sabato (CEO) and Yoav Ramon (CTO), develops an AI admin assistant – also called Catch – that the developers claim demonstrates AI agents can safely move beyond analysis and reporting toward active decision-making. It is designed to behave like a human executive assistant, and handles sensitive communications, scheduling, and personal data with the same level of care expected from a trusted executive assistant.

The executive user explicitly defines, during the onboarding process, which personal and workspace assets Catch can access. So, for example, if it is granted access to the executive’s inbox, calendar and travel accounts, it will monitor just these. But if it detects a flight booked with no hotel attached, its reasoning capabilities will proactively check rates at the executive’s usual hotel and ask whether to book it.

It is a human-like judgment call, keeping the human executive in the loop to maintain the agent’s boundaries.

Catch can coordinate with the executive’s guests to schedule meetings, book travel, and handle follow ups to correspondence. “Catch works out of the box within minutes of syncing – building a profile of the executive, who they work with, how they like to meet and travel, and starts acting on it over text, email, Slack or phone, with no new tool or UI to learn. Human input is only needed when a decision genuinely requires it,” explain the developers.

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The product provides an implicit argument for outsourced rather than self-built complex agents. With modern coding agents, executives can build their own agentic admin assistants, but it is questionable whether they can build a secure agent, or the security team can build adequate guardrails to secure the output without impacting the benefits. Outsourced agents could – in fact, should – be delivered ready made with the correct built-in security features.

In this case, the autonomy and security of Catch is constrained by multiple internal guardrails. It runs on a cloud infrastructure with layers of security, encryption, and monitoring to protect user data. It never performs actions outside the granted permissions, which can be amended at any time. It includes the executive human in the loop, similar to a human assistant saying to his boss, “You’re going to Memphis next week, should I book a room at this hotel for you?”

Catch uses single sign-on for authentication, with sensitive credentials and API keys stored in AWS Secrets Manager. All data is encrypted in transit and at rest, with AES-256 encryption while at rest – and it is continuously monitored for unusual activity, intrusion attempts, and abnormal API usage.

“Executives don’t want to build their own AI agents, and in the admin space, they don’t want to approve every step their assistant makes – they want it done right, in a way they can trust,” says Sabato. “Catch works alongside business leaders the way a great human assistant would, but 24/7, with no dip in attention and fully secure. We’re laser-focused on one thing – executive admin, making the right call in real time.”

Billed at $99/month, Catch claims an improved admin assistant at a fraction of the cost of a human assistant.

Related: DataBahn Raises $40 Million for Agentic Data Pipeline Management

Related: Mate Security Raises $35 Million for Agentic SOC

Related: UK Government Rolls Out Agentic AI Defense Plan Alongside Industry Pledge

Related: HiddenLayer Raises $100 Million for AI Runtime Security

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