Sweet Security, a pioneer in Runtime Cloud-Native Application Protection Platforms (CNAPP) and AI security solutions, announced that it has raised $75 million in Series B funding, led by Evolution Equity Partners, with participation from Munich Re Ventures, Glilot Capital Partners, and Key1 Capital. This brings Sweet Security’s total capital raised to $120 million.

The fresh funding will fuel global market expansion and accelerate product innovation to meet the rising demand for real-time protection across cloud infrastructure, AI systems, and production environments. Alongside the funding, Sweet introduced new AI security capabilities designed to protect models, agents, and the complete AI lifecycle—strengthening its leadership in the fast-evolving Runtime CNAPP and AI security ecosystem.

“Sweet Security stands out in one of the most competitive areas of cybersecurity,” said Richard Seewald, Founder and Managing Partner at Evolution Equity Partners. “Their unique approach to combining real-time cloud defense with AI-driven intelligence is redefining how enterprises secure both cloud environments and AI applications.”

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Driving a Shift Toward Runtime-First Cloud Security

As the CNAPP industry evolves toward runtime-first protection, Sweet Security has rapidly become a preferred platform for large enterprises—displacing legacy vendors and transforming how organizations protect production environments.

The new funding follows a year of explosive growth for the company, including a sixfold increase in annual recurring revenue (ARR) and a tenfold expansion in enterprise customer adoption, which now includes multiple Fortune 1000 companies.

Sweet Security also recently secured a U.S. patent for its technology that trains large language models (LLMs) to detect anomalous log sessions—dramatically reducing alert noise and identifying complex, multi-step attacks often missed by traditional rule-based systems.

Expanding Into AI Security With the Sweet AI Security Platform (AISP)

With agentic AI systems increasingly integrated into enterprise workflows, organizations face a growing array of new risks—from poor visibility to emerging attack vectors not seen in traditional microservices environments. To bridge this security gap, Sweet Security has launched its AI Security Platform (AISP).

AISP enables AI teams to discover every model and agent, monitor how they interact, and identify misconfigurations or excessive permissions before they escalate into security incidents. By extending its runtime-powered visibility from cloud workloads to AI systems, Sweet now delivers complete insight and control across both domains.

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Key capabilities of the AISP include:

Comprehensive AI Mapping: Automatically identify all AI agents, LLM servers, and connected services to uncover “shadow AI” and assess risk exposure.

  • Adversarial Defense: Detect and prevent prompt injection and other AI-specific attacks through AI-Driven Response (AI-DR) technology.
  • Behavioral Monitoring: Continuously analyze agent behavior to flag anomalies and block unauthorized actions in real time.
  • AI Infrastructure Hardening: Evaluate posture, recommend mitigation strategies, and apply guardrails that protect development without slowing innovation.

This unified approach allows organizations to build and deploy resilient AI systems that maintain both high performance and robust security by design.

Real-Time Protection for the Modern Enterprise

“No one protects runtime cloud and AI environments quite like we do,” said Dror Kashti, Co-Founder and CEO of Sweet Security. “Modern cloud and AI systems evolve in real time. Defending them requires a dynamic, continuous understanding of how models, agents, and workloads behave—not static snapshots of configuration data.”

James Berthoty of Latio Tech added, “Sweet Security has developed a best-in-class runtime protection solution that extends security coverage across cloud workloads, data, and AI applications—empowering organizations to safeguard both traditional and AI-driven environments with a single, cohesive platform.”

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