Production AI Guardrails
Security for every LLM call.
LLM Shield sits between your application and your LLM. Inspects inputs, enforces policies, scans outputs, and secures agentic tool-calling workflows — with per-tenant isolation, runtime audit, and compliance mappings out of the box.
19
Guardrails
13
Industry suites
~26K
Red-team prompts
<250ms
Inspection budget
Why LLM Shield
🛡️
Defense in depth
19 guardrails across input safety, output quality, and agentic security — composed into a two-tier parallel pipeline.
🏢
Built for multi-tenant
Per-tenant policies, rate limits, quotas, and audit logs persisted in Redis. Drop-in for SaaS or enterprise.
⚡
Fast where it matters
CPU guardrails run first under a 250ms budget. LLM-based checks fire only when needed.
🤖
Agent-native security
Role-based tool authorization, MCP server validation, data taint tracking, and goal-drift detection.
Where to start
| If you want to… | Go to |
|---|---|
| Spin it up in 5 minutes | Quickstart |
| Understand how it answers common buyer questions | FAQ |
| See every endpoint | API Reference |
| Pick the right deployment shape | Installation Guide |
| Run on-prem with HA | On-Premises Deployment |
| Wire up agents (LangChain / CrewAI / OpenAI) | Agentic Integration |
| Map to NIST / OWASP / ISO controls | Compliance Mapping |
Two deployment modes
- Full Shield (
Dockerfile) — GPU worker with llama.cpp + all guardrails + admin portals - Admin-only (
Dockerfile.admin) — Lightweight (~150 MB) portal + tenant APIs, no GPU. Runs anywhere (Cloud Run, Fly, Render, laptop).
Both share the same backend APIs and connect to the same Redis for tenant state.
┌─────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ Tenant App │──▶│ Full Shield │──▶│ Redis (Upstash │
│ (your AI) │ │ (GPU worker) │ │ or local) │
└─────────────┘ └──────────────────┘ └─────────────────┘
▲
┌──────────────────┐ │
│ Admin Portal │───────────┘
│ (lightweight, │ Per-tenant policies,
│ runs anywhere) │ rate limits, audit log
└──────────────────┘