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Most enterprises define AI policies and deploy controls — but never measure whether those controls actually work across live systems.



Singulr is a closed-loop control system that governs AI across your enterprise - from policy definition through runtime enforcement to adversarial defense. Three enforcement pillars do the work. An intelligence layer wraps around them, feeding context in and generating proof on the way out.
Every enforcement cycle tightens the system: discovery informs governance, behavioral patterns inform control, failure modes inform security, and security outcomes sharpen the entire loop.

Define enforceable intent: policies, ownership, risk thresholds — and validate it before it reaches production. When something drifts, accountability is already assigned.

Translate governance into real-time boundaries at the service, model, prompt, data, account, and agent levels. Then measure whether those boundaries are holding — not just whether they're configured.

Act on true adversarial risk — prompt injection, jailbreaks, data exfiltration — with full forensic traceability. Upstream enforcement has already resolved preventable events, so security operates on high-confidence adversarial signals.

The intelligence engine that makes the loop work and the proof system that shows it did. Singulr Pulse™ continuously discovers and classifies every AI asset across your environment — services, agents, MCP servers, embedded AI, local tools — and feeds that context into each pillar. On the way out, it generates longitudinal, tamper-evident evidence that controls operated as intended. EU AI Act, NIST AI RMF, SOC 2, GDPR — produced as a byproduct of the control system running.
A marketing analyst opens ChatGPT with a personal account
Singulr detects the personal account, blocks the session, and redirects to the enterprise-approved instance. The policy, the enforcement, and the outcome are all recorded.
An AI agent requests access to a customer database via MCP server
Singulr evaluates the agent's permission boundaries, the data classification of the target, and the policy governing that interaction. Access is denied. The governance team is notified. The agent's risk score is updated in Singulr Pulse™.
A prompt injection targets a customer-facing agent
Runtime Security detects the adversarial pattern, blocks the interaction, and creates a forensic trace linking the attack vector, the model response, and the enforcement action — all correlated with the agent's configuration history.
detect and respond, but do not govern cross-system AI interactions, route failures to the right team, or improve system strength over time. Security is consequence management. Singulr is systemic control.
govern their own ecosystem. They cannot control cross-cloud AI, embedded SaaS AI, employee-used tools, or provide independent cross-vendor assurance.
lead with detection and protection, but stop short of governance enforcement. They tell you what happened. Singulr ensures the right thing happened — and proves it.
