NVIDIA NeMo Guardrails vs Sanctum Runtime
NVIDIA NeMo Guardrails
developer.nvidia.comSanctum Runtime
sanctumruntime.comSide by side
| Figure | NVIDIA NeMo Guardrails | Sanctum Runtime |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | Yes | — |
| Web | — | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| iOS | — | Yes |
| Android | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 0 |
| Spec score · LLM Security Tools | 8.6 (#4) | 7.2 (#19) |
| Integrations | The documentation lists integrations with NVIDIA safety models, community models, third-party APIs, Python actions, and LangChain tools. | The same verification path is described for OpenAI, Claude/MCP, Gemini-style function calling, DeepSeek, Grok, Bedrock-compatible endpoints, NVIDIA NIM, custom agents, and local runtimes. |
| Intended users | The library is presented for developers and teams building LLM applications who need configurable policy enforcement and safety checks. | The site presents the product for agent startups, platform and AI engineers, and security or compliance teams. |
| Purpose | NeMo Guardrails is an open-source Python package for adding programmable guardrails to LLM-based applications. | Sanctum is a runtime trust layer that evaluates AI actions before they execute. |
Plans
NVIDIA NeMo Guardrails
- Open-source NeMo Guardrails libraryFree
- Open-source NeMo Guardrails libraryFree
- NeMo Guardrails microservicePriced on request
In their own words
NVIDIA NeMo Guardrails
NVIDIA NeMo Guardrails is an open-source Python package for adding programmable policy and safety checks to applications built with large language models. It can block, alter, or validate inputs and model responses that are unsafe, off-topic, malicious, or against configured policies. Its rails cover input, retrieval, dialog, execution, and output stages. Developers can configure behavior with YAML files, Colang flows, built-in guardrails, and custom actions. The catalog includes content safety, jailbreak protection, topic control, PII detection, agentic security, tool calling, hallucination and fact-checking, and model self-checks. Applications can use the Python SDK or a Guardrails server with HTTP endpoints such as OpenAI-style chat completions. The library supports Windows, Linux, and macOS, and can run in a self-managed Python environment. The installation guide lists Python 3.10 through 3.13 and at least one CPU with 4GB RAM; external models may require separately deployed GPUs. The open-source library costs nothing, though external models and services may need separate setup. NVIDIA cautions that no single rail covers every adversarial prompt and advises defense in depth and evaluation.
Sanctum Runtime
Sanctum Runtime is middleware that checks actions from AI agents, robots, and automated systems before they are carried out. It evaluates proposed actions against policies and can approve them, ask for verification, or block them. Operators can review, approve, deny, or escalate actions through web and mobile workflows. The product describes behavioral monitoring, audit logs, policy history, and decision trails for runtime visibility and incident review. Its open-core runtime supports local policy checks and offline verification, including local Ollama risk scoring. Documented integrations include OpenAI, Claude/MCP, Gemini-style function calling, DeepSeek, Grok, Bedrock-compatible endpoints, NVIDIA NIM, custom agents, and local runtimes. Developers can use Node and Python SDKs, an MCP wrapper, ROS2-oriented policy packs, and smart-home and embodied-agent templates. The repository is described as MIT-licensed and self-hostable; a hosted console and proxy path are also available. The product identifies itself as embedded runtime middleware, not a standalone consumer app or robot controller. Some enterprise capabilities, including fleet orchestration and organization-wide policy sync, are private.