Eve Security

Name: Eve Security
Brand: Eve Security

AI Native

Secure the use of Agentic AI - Observe, Control, Trust

Est 2025|1 Ref Customers

LinkedIn 3K|Website|FTEs 20|HQ Austin, Texas, US

01Competitive Landscape

| Aspect | Eve Security (EveGuard) | Lakera Guard (Check Point AI security portfolio) | Protect AI (LLM Guard / AI security) | |--------|--------------------------|-----------------------------------------------|--------------------------------------| | Starting Price | Not publicly listed | Varies; not consistently public | Varies; not consistently public | | Best For | Enterprises seeking execution-time control over agent actions across tools and integrations | Teams focused on prompt injection/jailbreak/data leakage filtering between user/app and model | Teams seeking broader AI security coverage (guardrails, scanning, and governance components depending on vendor mix) | | Key Strength | Runtime enforcement framing; discovery + enforcement narrative; vendor indicates SOC 2 posture | Recognized in prompt-injection and model I/O filtering evaluations | Broad AI security tooling footprint; often included in LLM security assessments | | Key Weakness | Limited public third-party reviews; unclear pricing and detailed enterprise feature documentation; name collisions in public discourse | May be more focused on model I/O filtering than full cross-system action authorization | May be broader than needed for buyers seeking focused runtime authorization; integration depth varies |

Narrative analysis

Category clarity problem
- The market includes several distinct activities: governance/GRC (policy, compliance tracking), model evaluation and red-teaming, prompt-layer filtering, runtime action authorization, and discovery/inventory. Buyers should explicitly map vendor capabilities to the specific need (for example, runtime action authorization versus governance documentation).
Where Eve may be applicable
- If the product enforces policy at the execution boundary and can inspect and apply decisions to agent-initiated actions across frameworks and enterprise systems, it aligns more with authorization and runtime policy enforcement layers than with prompt-only filtering tools.
Where competitors may provide advantages
- Governance-heavy platforms typically offer more structured compliance workflows, reporting, and regulatory mapping.
- Established model/prompt security vendors may have more public benchmarks, community evaluations, and third-party usage narratives.

01Competitive Landscape

Aspect	Eve Security (EveGuard)	Lakera Guard (Check Point AI security portfolio)	Protect AI (LLM Guard / AI security)
Starting Price	Not publicly listed	Varies; not consistently public	Varies; not consistently public
Best For	Enterprises seeking execution-time control over agent actions across tools and integrations	Teams focused on prompt injection/jailbreak/data leakage filtering between user/app and model	Teams seeking broader AI security coverage (guardrails, scanning, and governance components depending on vendor mix)
Key Strength	Runtime enforcement framing; discovery + enforcement narrative; vendor indicates SOC 2 posture	Recognized in prompt-injection and model I/O filtering evaluations	Broad AI security tooling footprint; often included in LLM security assessments
Key Weakness	Limited public third-party reviews; unclear pricing and detailed enterprise feature documentation; name collisions in public discourse	May be more focused on model I/O filtering than full cross-system action authorization	May be broader than needed for buyers seeking focused runtime authorization; integration depth varies

Narrative analysis

Category clarity problem
- The market includes several distinct activities: governance/GRC (policy, compliance tracking), model evaluation and red-teaming, prompt-layer filtering, runtime action authorization, and discovery/inventory. Buyers should explicitly map vendor capabilities to the specific need (for example, runtime action authorization versus governance documentation).
Where Eve may be applicable
- If the product enforces policy at the execution boundary and can inspect and apply decisions to agent-initiated actions across frameworks and enterprise systems, it aligns more with authorization and runtime policy enforcement layers than with prompt-only filtering tools.
Where competitors may provide advantages
- Governance-heavy platforms typically offer more structured compliance workflows, reporting, and regulatory mapping.
- Established model/prompt security vendors may have more public benchmarks, community evaluations, and third-party usage narratives.

Eve Security

01Competitive Landscape

Narrative analysis

02Market Map

01Competitive Landscape

Narrative analysis

02Market Map