GLACIS vs Sanctum Runtime
GLACIS
glacis.ioSanctum Runtime
sanctumruntime.comSide by side
| Figure | GLACIS | Sanctum Runtime |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Linux | — | Yes |
| iOS | — | Yes |
| Android | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 0 |
| Spec score · LLM Security Tools | 7.8 (#9) | 7.2 (#19) |
| Who it serves | The signup form lists AI sellers serving healthcare or other regulated buyers, healthcare AI overseers, AI-agent builders or operators, and people evaluating the product. | The site describes the product for teams building AI agents, robotics, workflow automation, and other systems that can take real-world actions. |
Plans
In their own words
GLACIS
GLACIS puts controls in the path of AI actions and creates signed records of covered decisions for external verification. When an action crosses configured bounds, it can be constrained, held for a person, or denied; other actions can pass through unchanged. Glacis says it operates nine production components as a managed service alongside the identity provider, cloud, and security systems a customer already uses. Records use OVERT, a published open format that implementers and reviewers can inspect, and can be checked in a browser without a Glacis account. The site says payloads remain in the customer’s environment and records contain hashes; omitting protected fields depends on deployment setup. A record check does not establish whether an action was correct, whether every event was captured, or whether a system is safe or compliant. GLACIS is available by API, web, and self-hosted deployment. Its Free account costs nothing, with no card required. The contact page describes a six-week evaluation for a workflow under review.
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.