Model security vs. runtime governance. Protect AI secures models before deployment. Intercis enforces policy while agents act.
| Capability | Intercis | Protect AI |
|---|---|---|
| Deployment model | Intercept proxy (zero code changes) | Model scanning + supply chain tools |
| Tool call interception | ✅ Real-time deny/allow/observe | ❌ No runtime interception |
| Agent identity validation | ✅ Per-agent registry + tool scopes | ❌ Model-focused, not agent-focused |
| Tamper-evident audit trail | ✅ Policy decision logged per call | ⚠️ Model scan reports |
| OWASP Agentic AI coverage | 14/17 threats | ⚠️ T17 (Supply Chain) primarily |
| Prompt injection detection | ✅ Observe mode | ❌ Not their focus |
| Kill switch | ✅ Manual: deactivate agent, proxy denies calls | ❌ Not applicable (pre-deployment) |
| SOC2/ISO 27001 evidence | ⚠️ Audit log export; no SOC2/ISO packages | ⚠️ Model governance reports |
| Pricing | Contact for pricing | Enterprise pricing |
Protect AI is for teams focused on securing ML model training pipelines and supply chains. If you need to scan models for vulnerabilities, poisoning, or malicious code before deployment, Protect AI's Guardian and ModelScan products are industry-leading.
Choose Protect AI if your primary concern is catching compromised or poisoned models early. They excel at model governance, AI/ML bill-of-materials (SBOM), and supply chain security—preventing bad models from ever reaching production.
Protect AI is essential for teams working with open-source models, third-party fine-tuned models, or complex model pipelines where provenance and integrity matter.
Intercis is for teams that need to control what agents do at runtime. A clean, trustworthy model can still take destructive actions if it has tool access and no policy enforces boundaries.
Choose Intercis if you need real-time action-layer governance—before an agent deletes files, modifies databases, or triggers deployments. Intercis is your runtime safeguard once your model is deployed and acting in production.
Intercis solves the problem Protect AI doesn't: what happens when your agent makes a decision. An agent with tool access can cause harm even if its underlying model is benign. You need action-layer policy enforcement, not just model verification.
Protect AI secures the model. It scans for vulnerabilities, malware, poisoning, and supply chain risks. It answers: "Is this model safe to deploy?"
Intercis secures what the model does. It enforces policy on every tool call that crosses the LLM API wire, validates agent identity, and can deny destructive actions. It answers: "Should this agent execute this action right now?"
Different attack surfaces, complementary protections. A malicious model (Protect AI threat) is different from a benign model making a policy-violating action (Intercis threat). You can need both.
Request early access and watch how action-layer governance protects your agents.