Every industry.
One governed fabric.Enterprise AI security that governs every agent as a verifiable principal — one platform, one policy, one proof.

Enterprise AI security is the discipline of protecting an organization’s AI systems — models, applications and especially autonomous agents — and governing what they are allowed to do across every business unit. It spans identity for non-human actors, least-authority permissions, prompt-injection containment, data protection, auditability and compliance. RankShield delivers it as one governed fabric: every AI agent runs as a verifiable principal with bounded authority, every action is authorized against one policy, and every action emits a post-quantum-verifiable receipt — the same control plane across finance, healthcare and legal.

Because the model is rarely the weak point — the missing controls around it are. Gartner projects that over 40% of agentic AI projects will be canceled by the end of 2027, citing escalating costs, unclear business value and inadequate risk controls. IBM’s Cost of a Data Breach 2025 found 13% of organizations reported breaches of their AI models or applications, and 97% of those lacked proper AI access controls. The pattern is consistent: enterprises can build capable agents faster than they can govern them. RankShield closes that gap with identity, authorization and proof built in from the start.

Blast radius is how far a single compromised agent can spread before something stops it. An agent with standing permissions and implicit trust in other systems can, once hijacked by a prompt injection, move laterally — reading, deleting, paying or emailing across the enterprise. The defense is architectural: bound each agent’s authority, authorize every action, and treat agent-to-agent and agent-to-tool calls as governed requests. Under RankShield, a compromise is contained to the entry point and receipted, instead of cascading. You can see this modeled live on this page.

With one core and one policy engine, adapted to each domain’s stakes rather than rebuilt per silo. A payment agent is bound to pre-settlement intent limits; a clinical agent attests provenance without touching PHI in the clear; a legal agent isolates privileged material. In every case the mechanism is identical — verifiable identity, least authority, and a receipt for every action — which is why one platform can govern all three without the fragmentation that creates gaps. That shared fabric is also what lets the organization prove compliance consistently.

Traditional tools authenticate people and inspect network traffic; they were not designed for software that reasons in natural language and acts autonomously with its own credentials. Point solutions detect and alert after the fact. RankShield governs the action itself: it issues each agent a verifiable identity, enforces least authority before an action runs, contains prompt injection at the action layer, and produces a tamper-evident, post-quantum-signed receipt for every action. The difference is prevention-and-proof by architecture versus detection-and-hope after the event.

By producing the evidence frameworks ask for. The NIST AI Risk Management Framework (AI RMF 1.0) and its Generative AI Profile (NIST AI 600-1, July 2024) call for governance, mapping, measurement and management of AI risk, and NIST’s in-progress control overlays (COSAiS) extend SP 800-53 to AI systems including agents. RankShield’s verifiable receipts, bounded-authority policies and identity records give you a consistent, checkable audit trail that maps to those functions — supporting compliance rather than claiming to grant it, which no tool honestly can.

You treat every non-human actor as a first-class, governed identity. Machine identities already outnumber humans by roughly 82 to 1 (CyberArk, 2025 Identity Security Landscape), 42% hold privileged or sensitive access, and 68% of organizations admit they lack identity security controls for AI. RankShield enrolls every agent and service as a verifiable principal with a post-quantum-capable identity and a bounded manifest, so each one is authenticated, authorized and attributable — turning an ungoverned sprawl of keys and tokens into an accountable population.

No — it is the governance and proof layer for AI that sits alongside your stack. RankShield does not replace your firewalls, IAM or SIEM; it gives your AI agents an identity, bounds their authority, contains injection at the action layer, and emits verifiable receipts your existing tools and auditors can consume. It closes the specific gap that agentic AI opens — autonomous software acting with real permissions — which conventional controls were never built to govern.

No — and any vendor claiming that is not being honest. No platform can guarantee an LLM will never be manipulated or a system never compromised. RankShield’s promise is different and verifiable: contain the blast radius by architecture so a compromise can’t cascade, and prove every action with a receipt you can independently check. Security you can verify, not an unfalsifiable guarantee.