详细内容
Backed by Y Combinator
Make your AI safe. And prove it.
Protect against data leaks, prompt injections, and hallucinations.
And make it easy for your buyers to stay compliant.
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Infer
Stop failures where they start—inside your agents
You shouldn't have to choose between moving fast and staying safe. Guardrails run inside your agents to stop prompt injections, block data leaks, and catch bad outputs before they reach users.
Find the gaps before attackers do
Don't wait for an incident to find out your AI is vulnerable. Adversarial tests probe your system for prompt injection weaknesses, data leakage paths, and other attack surfaces, so you find the gaps before anyone else does.
Close enterprise deals without the safety objection
Procurement teams want proof that your AI won't leak data or behave unpredictably. Instead of scrambling to answer security questionnaires, share a Safety Page that shows your guardrails and test results from day one.
Three parts that work together
Guardrails
Small language models that run inside your agents. Guard stops attacks. Redact blocks leaks. Verify checks outputs.
Adversarial Tests
Adversarial tests that run on your schedule. Measure prompt resistance, data protection, and accuracy.
Safety Page
A public page showing your controls and results. Share it with prospects and procurement teams.
Simple, usage-based pricing
Guardrail models are billed on a usage basis according to token consumption. Pay only for what you use with transparent, per-token pricing.
| Model | Input tokens | Output tokens |
|---|---|---|
| Guard | $0.9 per million | $1.9 per million |
| Verify | $0.9 per million | $1.9 per million |
| Redact | $0.9 per million | $1.9 per million |
Frequently Asked Questions
Who is Superagent built for?
How quickly can I show something to a prospect?
What makes AI failures different from regular software bugs?
Why isn't SOC 2, ISO 27001, or ISO 42001 enough?
We already use GPT, Claude, or Gemini. Don't they have built-in safety?
What failures do the guardrails actually catch?
Do I need both guardrails and adversarial tests?
How much engineering work does this require?
What does it cost?
Latest Release
Lamb-Bench: See how your model stacks up
We test frontier LLMs on prompt injection resistance, data protection, and factual accuracy. Use it to pick the safest model for your product.
Make your AI safe. And prove it.
Book a call