Secure the AI in your applications — from the first commit to the live prompt.
Rulebound discovers every model, SDK and key across your code and cloud, surfaces the supply-chain and posture risks, red-teams your AI before attackers do, and guards it at runtime against injection and data leakage.
Illustrative. Values shown are synthetic test data.
Your teams are building AI into products every sprint — new models, new SDKs, new prompts. The attack surface grows with each merge, and most of it never reaches a security review before it reaches production.
AI dependencies get added faster than anyone can review them — new providers, libraries and keys land in the codebase with no inventory of what's actually running.
Hardcoded API keys, over-permissioned integrations and unvetted models sit in your repos and configs — a supply chain nobody has mapped.
The AI features you ship can be jailbroken, coerced by untrusted content, or made to leak customer data — straight through your own product.
Nothing connects what's in the code to what's exposed at runtime — so you can't prove an AI feature is safe before, or after, it goes live.
Rulebound follows each AI feature across its whole life — inventoried in the code, tested like an attacker, and guarded while it runs — so a finding at build time and an attempt at runtime live in the same picture.
Every finding and blocked attempt lines up with the frameworks your security team already reports against — build-time risk and runtime defense in one language.
Rulebound builds the inventory from your source and your cloud, then puts guardrails in the live path of your app's model calls.
Scan your repos for AI models, SDKs, hardcoded keys and risky configs — an AI bill of materials for everything you build.
Connect to your cloud to discover AI workloads on Kubernetes and managed services like AWS Bedrock and SageMaker.
Put the Rulebound gateway in front of your app's model calls with a single base-URL change — guardrails without an app rewrite.
Discovery, posture, red-teaming and runtime guardrails in a single platform — so a build-time finding and a runtime attempt sit in the same graph.
Attack your own AI apps with automated adversarial testing before an attacker does — and the findings feed the same posture, not a separate report.
Protect your app's model calls at the gateway with a base-URL change. No SDK to adopt, no code to change, no app to re-architect.
Application posture connects to usage, agents and compliance — one graph across every layer AI touches your organization.
Request access and we'll show you every model, SDK and key across your code and cloud — and exactly where an attacker would get in.
Securing the AI features your own teams build — across their whole lifecycle. Rulebound inventories the models, SDKs and keys in your code and cloud, scores their risk, red-teams the AI to find what breaks, and enforces runtime guardrails on the app's prompts and responses.
An AI bill of materials — a live inventory of the AI in your applications: models and providers, AI SDKs and dependencies, hardcoded keys, and risky configurations. It's the map that everything else — posture, red-teaming, runtime defense — is built on.
Both. We scan your repositories for models, SDKs, keys and configs, and connect to your cloud to discover AI workloads running on Kubernetes and managed services like AWS Bedrock and SageMaker. AI self-hosted on plain virtual machines is surfaced through the endpoint agent rather than the cloud scan.
No. Point your application's model calls at the Rulebound gateway with a single base-URL change. There's no SDK to adopt and no application code to rewrite — guardrails apply inline to the prompts and responses.
Automated adversarial testing against your own AI apps — prompt injection, jailbreaks, data-leakage and misuse — so you find the exploitable paths before an attacker does. Findings map to the OWASP LLM Top 10 and MITRE ATLAS and feed the same posture view.
Findings and blocked attempts map to the OWASP LLM Top 10, MITRE ATLAS and NIST AI RMF, alongside a live inventory of the AI in your applications.