Superagent

Real-time security and compliance guardrails for AI applications

4.7 (6)

مراجعة بواسطة Daniel Nikulshyn·تم التحديث مايو 2026

Observability Enterprise LLM Ops Compliance Developer Tools AI Security Guardrails

نظرة عامة

Superagent is a security layer designed to protect AI-powered applications from threats like prompt injection, data leakage, and policy violations. It sits between your app and its underlying models, inspecting traffic in real time to block malicious or non-compliant interactions before they cause harm. The platform targets teams building agents, copilots, and LLM features who need to meet enterprise security and regulatory requirements. By providing observability alongside active enforcement, it helps developers ship AI products faster while maintaining oversight of model behavior and user inputs. Integrations and policy controls let teams customize protections to their specific use cases, from blocking sensitive data exfiltration to enforcing content guidelines across multiple model providers.

الميزات الرئيسية

Prompt injection detection
Data leakage prevention
Customizable security policies
Compliance monitoring and logging
Multi-model provider support
Real-time request inspection

حالات الاستخدام

Block Prompt Injection Attacks

Inspect user inputs in real time to detect and block prompt injection attempts before they reach the underlying model, protecting agents and copilots from manipulation.

Prevent Sensitive Data Leakage

Monitor outgoing model responses to catch and stop leakage of confidential or regulated data, helping teams safely deploy LLM features on internal data.

Enforce Compliance Policies for AI

Apply customizable policies and maintain audit logs to meet regulatory and enterprise security requirements across AI-powered applications.

Unified Guardrails Across LLM Providers

Apply consistent security and policy enforcement across multiple model providers, letting teams switch or combine LLMs without rebuilding protections.

المزايا والعيوب

المزايا

Real-time threat detection and blocking
Helps meet compliance requirements
Works across multiple LLM providers
Combines monitoring with active enforcement

العيوب

Adds a layer of latency to requests
Primarily aimed at technical teams
Effectiveness depends on policy configuration

المراجعات

4.7

المتوسط من 6 تقييم.

سجّل الدخول لكتابة مراجعة.

Mei-Ling Wong

Solid for our team

We rolled this out across the team last quarter and helps meet compliance requirements. Prompt injection detection fits neatly into how we already work, and customizable security policies removed a step we used to do by hand. Adds a layer of latency to requests, which is the main caveat, but it has held up under daily use.

Omar Haddad

Does the job

Pretty happy overall. Prompt injection detection just works and helps meet compliance requirements. Adds a layer of latency to requests can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.

Elena Rossi

Does the job

Pretty happy overall. Multi-model provider support just works and combines monitoring with active enforcement. but no dealbreakers — I'd recommend it to a friend without hesitating.

Ingrid Bauer

Years in this space

I've evaluated a lot of these over the years. What stands out here is compliance monitoring and logging — handled better than most — and works across multiple LLM providers. Worth the time if this is your use case.

Pierre Dubois

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on real-time request inspection, and real-time threat detection and blocking caught me off guard. Effectiveness depends on policy configuration is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Fatima Zahra

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on customizable security policies, and helps meet compliance requirements caught me off guard. still, I'd recommend giving it a real trial.