BlinkOps Security Agent Builder enables organizations to create unlimited AI agents

BlinkOps launched No-Code Security Agent Builder, an enterprise platform that allows security teams to create an unlimited number of custom security agents tailored for their unique environments.

The platform gives organizations full control over how agents operate, what they access, and how they make decisions.

“With BlinkOps, you can augment your team with thousands of custom tailored agents,” said Gil Barak, CEO of BlinkOps. “The BlinkOps Security Agent Builder gives organizations the ability to create an army of agents tailored to your specific tech-stack, processes and procedures. In just a few weeks, our customers have already built over 200 unique agents, automating tasks across SOC, IAM, GRC, Cloud Security, Network Security and Vulnerability Management teams.”

The BlinkOps Security Agent Builder combines AI agents with deterministic workflows and agent-to-agent collaboration, giving teams a structured and scalable way to automate security operations without compromising control. BlinkOps’ powerful visual workflow interface and automation infrastructure empowers teams to implement their ideas to production-ready agents in a matter of minutes, delivering immediate impact and security.

Key innovations and capabilities include:

• Roles – task focused agents: Create specialized agents that provide consistent results by defining their roles and responsibilities for specific tasks (such as “Malware Analysis Agent” or “Insider Threat Investigator Agent”).
• Abilities – managed accessibility: Provide access to pre-built secure workflows, ensuring that agents can perform actions within the defined parameters, removing the need to give agents direct access to your company’s system credentials. The workflows can include “human in the loop” steps for approving sensitive actions.
• Knowledge – enhanced experience: Equips agents with a specific knowledge base by providing access to relevant documents, data sources, and past information to leverage organizational data for context and accuracy.
• Peer Agents – collaborative power: Allow agents to communicate and collaborate with each other to achieve complex tasks at scale. This allows for a more efficient and expert-driven automation strategy compared to a single, overloaded agent.
• Seamless integration within workflows: Easily incorporate agents into your existing automation workflows for analysis and decision making.
• Future-ready interoperability: BlinkOps is designed to be a friendly platform that interoperates with agents built on other platforms as well as native MCP support.

BlinkOps streamlines the creation of agents tailored to your environment, each designed for a specific role and fully aware of your systems, policies, and workflows you expose them to. This platform-centric approach produces agents that speak the language of your tools, encode your internal policies, and operate across your tech stack with full context. As a result, agents can determine their actions dynamically based on the situation at hand.

“BlinkOps’ AI Agent Builder gives organizations something they haven’t had before—a way to quickly and easily augment their teams with thousands of agents (aka virtual employees) that are fully aligned with their enterprise systems, policies, and processes,” says Tal Morgenstern, Partner at Lightspeed Venture Partners. “This level of automation and control is a game-changer for the security industry that needs to always move fast without losing control.”

BlinkOps combines non-deterministic agents with deterministic workflows to support a modular automation model. Instead of relying on a single, overloaded agent, teams can distribute tasks across focused agents that collaborate to solve complex problems. This architecture allows organizations to scale security operations by offloading repetitive work, while focusing human effort on higher-level analysis and decisions.

By automating security workflows in a controlled and auditable way, BlinkOps helps organizations reduce manual effort, minimize errors, and mitigate risks often associated with AI adoption.