Best Agentic Cybersecurity Platforms for Cloud - Page 2

Reclaim Security is an AI-driven cybersecurity platform designed to automatically identify and fix security exposures across an organization’s existing security tools and infrastructure. Instead of simply detecting vulnerabilities or generating alerts, it focuses on automated remediation, helping security teams resolve misconfigurations, enforce security policies, and reduce risk without requiring extensive manual intervention. It scans the organization’s security stack, including cloud environments, identity platforms, endpoint protection tools, and other defenses, to identify gaps, weak configurations, or ineffective controls that could be exploited by attackers. Once risks are detected, it analyzes them in the context of real-world attack techniques and prioritizes the issues that pose the greatest threat. It then proposes remediation actions and can automatically deploy those changes once approved, ensuring security configurations remain optimized.

Kai is an agentic AI cybersecurity platform designed to transform how organizations defend against modern cyber threats by replacing fragmented security tools with a unified system that can autonomously reason, analyze risk, and execute defensive actions. It was built from the ground up to address the limitations of traditional security stacks, where teams rely on many disconnected tools, dashboards, and manual workflows that cannot keep up with the speed and complexity of AI-driven attacks. Kai uses agentic artificial intelligence systems that continuously contextualize security data, assess risks, reason about threats, and take action across multiple security domains, including threat intelligence, exposure management, detection, and incident response. Instead of acting only as a monitoring dashboard, it performs the actual security work by orchestrating data, tools, and workflows into a single pipeline that operates at machine speed.

Bold is an AI-driven endpoint security platform designed to protect enterprise devices such as laptops and workstations by deploying an autonomous security agent directly on the endpoint. It continuously monitors how users interact with applications, files, and data on the device, enabling it to detect unusual or risky behavior in real time rather than relying solely on traditional cloud-based monitoring tools. Because the AI agent runs locally on the device, it can observe every workflow and application activity without gaps caused by unsupported APIs or external integrations, providing full visibility into user actions and system behavior. When the platform detects a potential security risk, it does not simply generate an alert but can automatically enforce protective actions, turning threats into resolved incidents before they escalate into breaches.

Manifold Security is an AI Detection and Response platform built to secure autonomous AI agents operating on enterprise endpoints, addressing a critical gap in traditional cybersecurity approaches that focus primarily on user activity or model inputs and outputs. It provides runtime visibility into what AI agents actually do, capturing their behavior as they interact with systems, execute commands, access files, and call APIs across development environments and production infrastructure. Observing agent activity directly on endpoints without requiring additional infrastructure such as proxies or gateways, it enables organizations to monitor real actions rather than just prompts or responses. It maps relationships between agents, tools, and connected services, offering a clear view of which agents are active, what permissions they use, and how they interact with internal and external resources.

Raven is a runtime application security platform designed to protect cloud-native applications by operating directly inside the application during execution, rather than relying on external defenses. It provides real-time visibility into how code actually runs, allowing it to understand execution flows, libraries, and function-level behavior in order to detect and stop malicious activity before it occurs. Unlike traditional tools such as WAF or EDR that monitor from the outside, Raven embeds itself within the application, enabling it to prevent exploits, supply chain attacks, and zero-day threats even when no known vulnerability or CVE exists. It continuously monitors runtime behavior, identifies abnormal patterns or misuse of legitimate logic, and responds immediately to block harmful execution. It also helps teams prioritize security efforts by filtering out the majority of irrelevant vulnerabilities and focusing only on those that are truly exploitable.

Surf AI is a security operations platform designed to eliminate exposure and automate remediation by connecting context across all enterprise systems and turning fragmented risks into actionable workflows. It addresses the core problem behind growing security backlogs by identifying that the issue is not a lack of people, but a lack of unified context, and solves it by integrating systems, mapping dependencies, and assigning ownership to every issue. It operates through a continuous cycle of sensing data across systems, understanding ownership and relationships, reasoning about impact before action, and fixing issues through safe, automated remediation. By connecting tools and data sources, Surf enables teams to trace every exposure to a real owner and drive resolution end to end without relying on tickets or manual handoffs between teams. It automates workflows across systems, significantly reducing time spent on follow-ups and operational overhead.

CodeWall is an AI-powered autonomous penetration testing platform that continuously finds and validates security vulnerabilities in your applications. Unlike traditional point-in-time pentests, CodeWall deploys AI agents that autonomously map attack surfaces, chain real exploits, and deliver verified proof-of-concept evidence — running continuously alongside your change management and development cycle. Key capabilities: automated reconnaissance and subdomain enumeration, multi-phase exploit chaining, authenticated testing, AI/LLM vulnerability detection, and compliance-tagged findings. Supports web apps, REST/GraphQL APIs, cloud infrastructure, and internal tooling. Integrates with CI/CD pipelines via CLI and REST API.

Strike48 is the Agentic Operations Platform combining complete log visibility with customizable AI agents that run security, IT, and compliance operations at machine speed. Most organizations monitor only about 60-70% of their environment because traditional SIEM and observability platforms make full log coverage cost-prohibitive. Strike48 closes that visibility gap with architecture that decouples storage from upfront parsing decisions, letting teams ingest and retain all their logs without breaking budgets. Bring your logs or query them where they already live (Splunk, data lakes, cloud, on-prem), no rip-and-replace required. On top of that unified data layer, Strike48 deploys autonomous AI agents that run investigations, correlate and triage alerts, collect evidence, generate and validate detection rules, and hand work off to each other. A human-in-the-loop model ensures people approve critical actions like endpoint isolation and remediation, with full audit trails.

Snapper is an AI agent security platform designed to provide end-to-end governance and protection for organizations deploying AI agents across applications, networks, and systems. It delivers runtime enforcement by evaluating every agent action, including tool calls, API requests, and data access, before execution through a policy-driven rule engine with multiple enforcement layers. It offers unified visibility into AI usage by monitoring network traffic, browser activity, DNS, and processes to detect unauthorized tools and “shadow AI,” while also intercepting outbound LLM requests through SDK wrappers and a network proxy to evaluate, redact, and log sensitive data in real time. Snapper includes advanced threat detection capabilities that identify prompt injection, exploit chains, anomalous behavior, and multi-step attack patterns using behavioral baselines, kill chain tracking, and composite trust scoring.

Proofpoint AI Security is a unified platform designed to help enterprises govern, monitor, and protect the use of AI systems, large language models, and autonomous agents across the organization. It provides visibility into both sanctioned and unsanctioned AI usage, enabling security teams to discover shadow AI tools, observe prompts and responses, and understand how AI interacts with sensitive data in real time. It applies intent-based detection and behavioral analysis to identify anomalies, prompt injection attempts, and risky interactions, while enforcing policies directly during runtime to prevent data leakage and misuse. It reconstructs full AI transactions, from user input to agent actions and outcomes, giving organizations complete traceability and audit readiness. With controls that extend across endpoints, browsers, and AI agent connections, it enables granular access governance and ensures that AI systems only access and share appropriate information.

Straiker is an AI-native security platform built specifically to protect enterprise AI applications and autonomous agents, focusing on the emerging risks of “agentic AI” systems that interact with tools, APIs, and sensitive data. It provides full visibility and control across the entire AI stack by analyzing behavioral signals from models, prompts, tools, identities, and infrastructure, enabling real-time detection and prevention of AI-specific threats such as prompt injection, privilege escalation, data exfiltration, and malicious tool usage. It combines continuous discovery, adversarial testing, and runtime protection through core components like Discover AI, Ascend AI, and Defend AI, which together identify all active agents, simulate attacks to uncover vulnerabilities, and enforce real-time safeguards during execution. Its multi-layered architecture captures deep contextual signals across user interactions, networks, and agent workflows.

Ocean is an agentic email security platform that prevents AI-powered targeted attacks, automates triage, and gives employees real-time guidance. Traditional defenses scan the surface for anomalies and patterns that AI is now trained to avoid, while Ocean goes deeper by investigating every email before it reaches the inbox, not after the damage is done. Its central intelligence engine, Ray, coordinates a swarm of purpose-built agents that understand intent, enrich context, and follow the evidence across infrastructure, files, abuse mailboxes, links, identity, financial signals, quarantine, and contacts. Ocean builds a living memory of how an organization operates and communicates, adapts from day one, and constantly learns. Every verdict comes with the full reasoning behind it, every signal checked, and every step taken, backed by evidence instead of a score or black box.

With deployments covering mission-critical workflows, Norm Ai understands the importance of regulatory compliance. Norm Ai agents empower compliance teams to access and implement the most comprehensive and up-to-date understanding of regulations, accelerating business outcomes. Risk and compliance challenges are evolving, placing stress on compliance teams to acquire new expertise. Norm Ai agents are constantly gaining new regulatory skills so you can benefit from an ever-expanding toolkit. Norm’s proprietary AI stack ensures unparalleled regulatory comprehension by our AI agents. Operating within networks of large language learning models, our AI Agents can make immediate compliance determinations, undertake complex multi-step tasks, and provide actionable feedback grounded in deep regulatory understanding.

Arambh Labs is an agentic AI platform built to transform security operations from reactive firefighting into intelligent, proactive defense. The system deploys specialized AI agents — such as Byte, Rook, Echo, and Talon — each with distinct roles in alert response, strategic planning, threat hunting, and intelligence gathering. By correlating signals across identity, data, endpoints, networks, and cloud environments, the platform delivers full visibility into an organization’s security posture. Its intelligent prioritization ensures that teams focus only on the risks that truly matter, eliminating alert fatigue. Agentic remediation capabilities allow threats to be contained and vulnerabilities fixed at machine speed, drastically reducing mean time to response (MTTR). Backed by ex-Googlers and Fortinet engineers with patented expertise, Arambh Labs is enterprise-ready, scalable, and trusted by leading global security teams.

CrowdStrike Charlotte AI is an advanced, AI-driven cybersecurity solution designed to enhance threat detection and response by leveraging machine learning and behavioral analysis. It continuously monitors network activity, endpoints, and cloud environments to identify patterns and anomalies that could indicate malicious behavior or potential cyber threats. By using advanced algorithms, Charlotte AI can predict and detect sophisticated attacks in real-time, reducing response times and improving overall threat prevention. Its ability to analyze vast amounts of data and provide actionable insights allows security teams to proactively address vulnerabilities and prevent incidents before they occur. Charlotte AI is part of CrowdStrike's broader suite of cybersecurity tools, helping organizations stay ahead of emerging threats with cutting-edge, automated defense capabilities.

Spectrum enables security teams to manage the full detection lifecycle, across any SIEM, data lake, or tool. From identifying what needs to be detected, to building it, deploying it, and making sure it keeps working. Spectrum continuously monitors your threat coverage against real-world threats, internal findings, and the realities of your environment, surfacing the gaps that matter. Emerging threats. Coverage gaps. Red team findings. Custom apps. Spectrum analyzes them all and builds a detection strategy tailored to your environment and stack. It authors production-grade detections customized to your environment and data. Across any source, from strategy to deployment-ready, automatically. It continuously monitors every deployed detection, identifies drift, tunes for accuracy, and keeps coverage healthy through any change. No silent failures.