What Is Agentic AI — and Why Does It Matter Now?
Agentic AI refers to AI systems that can reason, plan, call tools, and execute multi-step tasks autonomously. Unlike traditional AI assistants that only respond reactively, Agentic AI takes initiative across systems — querying internal databases, calling third-party APIs, making conditional decisions, and collaborating with other agents to complete cross-functional workflows. The AI agents MaiAgent has deployed for over 100 enterprises across finance, healthcare, aviation, and manufacturing all operate on this architecture.
Over the past two years, the question enterprises ask about AI has shifted from "can we use it" to "can we trust it with real work." As AI evolves into Agentic AI — systems that reason autonomously, call tools, integrate APIs, and execute multi-step tasks — a new question takes center stage: can this AI that acts on its own actually be trusted?
MaiAgent has been thinking about this question. To address it directly, we have formed a global strategic partnership with cybersecurity leader Radware, integrating MaiAgent's enterprise AI Agent platform with Radware's Agentic AI Protection solution to help enterprises scale AI agents while building the security and governance architecture that scaling demands.
But every step toward autonomous action introduces a new dimension of risk.
Autonomous Action Introduces a New Category of Risk
When an AI agent does more than answer — when it actually calls tools, accesses data, and influences business outcomes — an enterprise's attack surface and governance scope expand in lockstep. Traditional application security and LLM-protection solutions were not designed for this.
The specific challenges we see across customer deployments include:
Prompt manipulation and agent abuse — attackers craft inputs that steer agents into unauthorized actions.
Tool and API misuse — agents may call sensitive APIs in the wrong context, leaking data or destabilizing systems.
Over-privileged agents — without granular policy controls, agents may hold access far beyond what their tasks require.
Lack of behavioral visibility — agent decisions, dependencies, and long-term behavioral trends often lack unified monitoring and audit.
Data leakage and compliance risk — in highly regulated industries such as finance and healthcare, the way agents handle personal data must be verifiable and auditable.
Without runtime governance, behavioral monitoring, and agent-aware protection, the faster an enterprise scales, the larger the exposure.
Why MaiAgent Chose to Partner with Radware
MaiAgent's own security posture is not weak: we are ISO 27001 and 27701 certified, with full RBAC and SSO, comprehensive audit logs, and on-premises and private-cloud deployment options, alongside an Agentic RAG (a retrieval architecture that lets AI autonomously decide which knowledge sources to draw from before answering) engine with approximately 95% response accuracy. These capabilities address "how agents are built, deployed, and governed" — but that is only half of what enterprise Agentic AI security requires.
The other half — and the layer most enterprises overlook — is this: at the moment an agent runs in production, every decision and every tool call must be evaluated — is it within policy? Is it being manipulated? Is it anomalous?
That requires real-time detection and intervention at the behavioral and intent level — Radware's core capability in cybersecurity.
Radware's Agentic AI Protection solution provides:
End-to-end visibility across the agent ecosystem — continuously discovering newly deployed agents and monitoring actions, tool usage, and dependencies.
Patented behavioral, intent-based detection — identifying prompt attacks, anomalous actions, and agent abuse in real time.
Continuous AI Security Posture Management (AISPM) — dynamically assessing risk, prioritizing exposures, and enforcing policy across agents and tools.
Broad integration across home-grown and SaaS agents — ensuring enterprises are not locked into a specific stack.
The two companies' capabilities are genuinely complementary: MaiAgent delivers the enterprise-grade agent platform and contextual intelligence; Radware delivers continuous safety guardrails at runtime. Together, they form full-lifecycle protection from build to action.
Three Industry Scenarios: Finance, Healthcare, Aviation
The partnership is not abstract. We have mapped concrete use cases and joint value across the three industries most actively deploying Agentic AI today.
Financial Services
Agent use cases in finance include AI investment assistants, credit-card concierge agents, and compliance copilots. MaiAgent grounds agents in financial products, policies, and regulatory documentation; Radware continuously monitors and blocks prompt injection and tool misuse, while supporting alignment with global standards such as GDPR and NIST.
Healthcare
From clinical decision support and nursing workflow agents to medical-documentation automation, MaiAgent embeds medical standards and internal SOPs into agents; Radware adds HIPAA-grade real-time protection, detecting anomalous or dangerous agent actions and ensuring patient data is handled safely across LLM workflows.
Aviation and Transportation
From booking and ticketing to real-time flight-status management and post-flight customer experience automation, MaiAgent connects agents directly to live CRM and reservation systems; Radware enforces strict runtime controls, blocking unauthorized tool calls and ensuring agents act only within validated boundaries in this safety-critical environment.
How MaiAgent Helps You Deploy Agentic AI Securely
For enterprises evaluating or already deploying AI agents, this partnership means three things:
Build agents on the MaiAgent platform that match your business logic — using AI KM (MaiAgent's enterprise knowledge management platform) to build the knowledge foundation and Agent Dev Kit to deploy business agents rapidly — while gaining Radware's runtime behavioral monitoring and protection.
Stop choosing between "moving fast on AI" and "staying compliant and secure."
Cross-industry, cross-system Agentic AI deployments come with a pre-integrated security backbone from day one.
This is the right time to talk to us about your 2026 rollout plans.
Frequently Asked Questions
What is Agentic AI?
Agentic AI is an AI system that can reason, plan, and execute multi-step tasks autonomously — calling tools, accessing data, and collaborating with other agents across systems, rather than just answering questions reactively.
How should enterprises evaluate the security of AI agents?
Evaluation should cover two layers: the platform layer — including certifications such as ISO 27001, RBAC, SSO, and private deployment options; and the runtime layer — behavioral monitoring, prompt-attack detection, and cross-agent policy enforcement. MaiAgent combined with Radware addresses both layers with a complete evaluation framework.
MaiAgent already has security certifications. Why is Radware still needed?
MaiAgent's certifications and features address the platform layer (ISO 27001/27701, RBAC, SSO, private deployment); Radware adds behavioral-layer protection at runtime — prompt-attack detection, anomaly detection on agent behavior, and policy enforcement across agents. The two are complementary, not overlapping.
What does this partnership mean for existing MaiAgent customers?
Existing customers can adopt Radware Agentic AI Protection's runtime security progressively, without changing their underlying platform.
Is this partnership only for large enterprises?
Not necessarily. While finance, healthcare, and aviation are our initial focus industries, any enterprise deploying AI agents into core business processes faces similar risk and governance requirements.
References
MaiAgent customer deployment data (internal statistics, as of Q4 2025)
Radware Agentic AI Protection product documentation
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