Check Point Embarks on a Mission to Transform Network Security Management with its Agentic Network Security Orchestration Platform, to Replace Decades of Rule-Based Complexity

As enterprise networks approach the limits of human-driven management, Check Point moves the industry from rules to intent, from fixed controls to dynamic prevention, and from fragmented consoles to unified orchestration

Check Point Software Technologies Ltd., a pioneer and global leader in cyber security solutions, launched its Agentic Network Security Orchestration Platform, a purpose-built autonomous agent architecture that executes network security operations across enterprise environments, without requiring constant human intervention. The launch continues the company’s mission to fundamentally transform the way enterprise network security is managed, an approach that has remained largely unchanged since the early days of the firewall era.

Enterprise networks have grown beyond human capacity to manage. Hybrid cloud adoption, M&A-driven fragmentation, the explosion of connected devices, and the rapid proliferation of AI agents across infrastructure have created environments that no human team was designed to secure at this scale. A single change request can take two to four weeks to work through analysis, security review, and policy dependencies – only to break something else and restart the cycle. Segmentation projects sit on the board for years and never ship. Policies drift because workloads move faster than any team can follow. The result is predictable: Zero Trust projects stall, policy tightening never completes, and organisations are left exposed. Check Point’s platform addresses this by beginning a transformation across three dimensions that have defined and constrained network security management for decades: moving from thousands of static rules to intent-based policy, from fixed threat prevention profiles to dynamic exposure-based controls, and from fragmented vendor consoles to a single orchestration layer across the entire network. Security teams set the business intent. The agents handle everything below it.

“For the first time, security teams can operate entirely at the level of business intent,” said Jonathan Zanger, Chief Technology Officer at Check Point Software Technologies. “With Agentic Network Security Orchestration, teams define what needs to be protected and what the policy should achieve. Everything below that, the rule creation, the policy tightening, the virtual patching, is handed to AI agents to execute autonomously, within predefined guardrails and under continuous human oversight. We are turning projects that used to take months into days of auditable action.”

Also Read: CIO Influence Interview with Kyle Wickert, Field CTO at AlgoSec

“Enterprise network security has reached an inflection point. Layering agentic AI on top of modern hybrid environments creates complexity that outpaces the capabilities of what human teams can manage manually. The consequence is that critical security initiatives like Zero Trust and micro-segmentation languish in administrative density and stall before they deliver value. Agentic approaches like Check Point’s ground autonomous execution in a live understanding of the actual network environment, representing a meaningful architectural shift in how organizations’ can structurally close that gap.” Frank Dickson, Group Vice President, Security and Trust, IDC.

At the center of the platform is a proprietary Network Knowledge Graph, a live, relational model of the customer’s actual environment, continuously updated with topology, traffic flows, asset dependencies, and real-time configuration data. This is what separates Check Point’s agents from generic AI applied to security problems. Rather than reasoning over static training data, agents reason over the customer’s actual network as it exists right now, grounding every decision in the customer’s specific reality.

The platform’s semantic intelligence layer goes further, interpreting not just the syntax of existing firewall policies but the business intent behind them, including rules created years or decades ago. Once that intent is understood, agents act on it autonomously across four core capabilities:

• Intent-to-Policy translates natural language business requirements into hardened, risk-validated firewall rules across multi-vendor environments.
• Zero Trust and Policy Tightening continuously analyses active traffic to identify shadow access and over-permissive configurations, autonomously applying validated tightening recommendations without risking connectivity breaks.
• Autonomous Troubleshooting conducts multi-step reasoning across topology, policy history, and logs to diagnose failures autonomously, reducing mean time to resolution from hours to minutes.
• Continuous Compliance maps every rule and configuration change to DORA, PCI-DSS, and NIST in real time, replacing annual audit fire drills with continuous automated enforcement.

Security teams retain authority at the intent level, approving high-impact changes before execution, with full visibility into every agent’s action through a complete execution trace. Underlying the platform are agent skills fine-tuned on more than 30 years of operational expertise protecting over 100,000 organisations, spanning the edge cases and configuration complexity that generic models have never encountered.

Accelerating the Roadmap: The Acquisition of Deepchecks’s Team and Intellectual Property

As part of the commitment to deliver on the Agentic Network Security Orchestration roadmap, Check Point has signed a definitive agreement to acquire the team and intellectual property of Deepchecks, a production-grade platform that unifies evaluation, observability, testing, and monitoring, giving teams the visibility and control needed to trust agents in production. The team is comprised of LLM experts, graduates of the prestigious Talpiot technological excellence program. Deepchecks’ talent and intellectual property will significantly accelerate the execution of the Agentic Network Security Orchestration roadmap.

“Any multi-agent system must include a robust evaluation layer that enables continuous measurement, tuning, and improvement over time,” explained Ofir Korzenyak, VP AI Technologies. “Deepchecks’ team brings cutting-edge capabilities precisely in this area, strengthening our ability to deliver agents that continuously improve and can be fine-tuned to customers’ specific needs.”