AgentGuard vs CrowdStrike & SentinelOne: Endpoint Giants Don't Understand AI
Key takeaways
- →CrowdStrike and SentinelOne are excellent at endpoint threats. AI agents run in clouds, SaaS and pipelines, not on laptops.
- →Their AI add-ons mostly inspect prompts. AgentGuard secures the Principals that create agents and enforces task context on every action.
- →EDR-based AI security needs heavy sensors and platform lock-in. AgentGuard is non-intrusive and deploys in days.
- →Policies are tuned per customer, not shipped as one global rule set.
Built for a different threat
CrowdStrike Falcon and SentinelOne Singularity were built to catch adversaries running code on hosts: process trees, memory injection, lateral movement, ransomware. Both have since added AI-focused modules, through acquisitions and new SKUs, that inspect prompts and employee AI usage.
Agentic attacks don't trip host telemetry. A compromised agent runs no malicious binary. It calls approved APIs with valid credentials, because something in its input told it to. Endpoint telemetry sees a normal process making normal HTTPS calls.
| Capability | Andeavour AgentGuard | CrowdStrike | SentinelOne |
|---|---|---|---|
| AI Principal security | Yes | No | No |
| Where it sees | Clouds, SaaS, pipelines, agents | Endpoints + AI add-on | Endpoints + AI add-on |
| Indirect injection & task-context checks | Per action | Prompt inspection | Prompt inspection |
| Deployment footprint | No sensor, zero integration | Kernel sensor + platform | Agent + platform |
| Customer-specific policy | Built per customer | Global detections | Global detections |
| Cost model | Agentic security only | Platform + SKUs + ingest | Platform + SKUs |
Prompt filtering is not agent security
Inspecting prompts for jailbreak strings catches the noisy attacks. It misses the ones that matter: indirect injection hidden in a document, a poisoned fine-tuning set, an orchestrator quietly changed to grant a new tool, or a SaaS vendor that switched on an autonomous feature in your tenant last Tuesday.
AgentGuard works at the layers EDR can't reach. It discovers shadow and injected agents, maps each one to its AI Principal, verifies the integrity of the training pipeline, and blocks actions that don't fit the agent's current task.
- Shadow agent discovery across clouds, SaaS and code repositories
- AI Principal mapping: who created, trained and commands every agent
- Training-pipeline integrity and poisoning detection
- Per-action task-context enforcement with blast-radius containment
Intrusive by design
Platform AI security from EDR vendors assumes you run their sensor everywhere and route telemetry into their data lake. That means deployment projects, kernel-level agents and deeper lock-in every year. Many security teams still remember a single faulty content update taking down millions of Windows machines worldwide in 2024. More kernel-level reach isn't automatically more safety.
AgentGuard installs no endpoint sensor. It sits next to your existing stack and observes agent behavior where agents actually run.
One rule set for everyone vs policy built for you
Global platforms ship global detections. Your agents, data classes and business processes are specific to you, and so are your acceptable behaviors. Andeavour builds and tunes AgentGuard policies for each customer, including vertical agents for regulated workflows, so enforcement reflects how your business actually runs.
Total cost
Adding AI modules to an EDR platform means paying for more SKUs on top of a premium platform, plus the data ingestion to feed them. You still end up without AI Principal coverage. With AgentGuard you pay for agentic security, and nothing else.
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