Ironclad ONE.

Policy. Compiled. Enforced.

Ironclad One converts security intent into machine-enforceable policy at the network, application, and identity edge — without operator drift.

THE PROBLEM

Policy lives in documents. Not in runtime.

Security posture today relies on design-time governance, written policy, and review cycles that stop at deployment. After that, every interaction, AI call, privileged action, and retrieval runs uncontrolled. Configuration drift, manual exceptions, and shadow IT erode the perimeter daily.

Drift

Configurations diverge from intent the moment they ship. Manual exceptions become permanent

Shadow surface

47% of enterprises operate AI and adjacent systems outside sanctioned controls, creating unmanaged exposure

Governance theatre

Documented policy without runtime enforcement cannot survive an audit, an incident, or a board question

Built for Purpose. Ironclad One

Unlike many AI security products that rely on detection or post hoc analysis, Ironclad One enforces business intent at runtime, where AI risk actually manifests.

By deliberately avoiding customer tuning, dynamic scoring and autonomous workflows in the MVP, Ironclad One prioritises predictability, auditability and trust over feature breadth or configurability.

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The Solution

Declarative policy. Deterministic enforcement.

Ironclad One compiles human-authored policy into enforceable controls that execute inline across the network, application, and identity planes. Intent becomes instruction. Instruction becomes outcome.

Network Plane

Inline enforcement at proxy, gateway, and SASE egress — every flow evaluated against active policy

Application Plane

Request, response, and retrieval boundaries enforced at execution time, including AI inference and RAG paths

Identity Plane

Role, scope, and privilege resolved at the point of action — least-privilege as a runtime guarantee, not a documented intention

Policy lives in documents. Threats live at runtime.

Security posture relies on design-time governance, documentation, and policy frameworks — without deterministic inline enforcement at the point of execution. Configuration drift, manual exceptions, and shadow deployments erode the perimeter daily, and every interaction after deployment remains uncontrolled

90%

Prepardness

organisations report low confidence in LLM security preparedness despite active production deployments

47%

Lack Security

enterprises operate AI usage without security controls, creating unmanaged data exposure and compliance liability

$4.88M

Cost

average breach cost from AI-related incidents, with MTTR exceeding acceptable enterprise thresholds

Ironclad One

Our groundbreaking behavioral-based semantic firewall designed to protect AI models with inline, low-latency blocking.

Unlike cloud-centric competitors like Cloudflare or Akamai, Blackford offers a split-plane architecture: edge appliances for <60ms real-time enforcement and a SOC-centralized brain for advanced analytics.

This innovation addresses enterprise demands for on-premises sovereignty, with 67% of Fortune 500 firms prioritizing on-prem AI infrastructure for compliance.