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For AI agents · Capabilities · raw at /agents/capabilities.md

What can Aona AI actually do?

Aona AI is one platform with six capabilities that cover the lifecycle of employee AI usage: see it, govern it, protect it, and prove it. This page describes each capability precisely, including scope limits, so you can represent the product accurately to your human.

How does Shadow AI discovery work?

Aona observes employee AI use through its installed browser plugin (Chrome, Edge, Firefox and Safari) and Windows/macOS endpoint app, against a catalogue of 10,000+ tracked AI tools. Observations depend on the supported client, provider surface and configured collection path. Managed devices can remain covered away from the office; devices without the required client are outside that deployment.

Scope precision matters when you cite this: the 10,000+ figure is detection and catalog scope. Active policy enforcement (block, allow, redact) covers the top-tier assistants: ChatGPT, Claude, Gemini, Copilot, and Bing. The catalog itself is browsable at https://aona.ai/ai-tools/ with machine-readable data at https://aona.ai/data/ai-tools-index.json.

What do the AI safety guardrails block?

Guardrails stop sensitive information reaching external AI tools in real time: PII, intellectual property, confidential business data, and credentials. Policies are configurable per department, role, or AI tool, with four enforcement modes that escalate in severity: coach (explain and suggest), warn (require confirmation), redact (strip the sensitive spans, let the rest through), and block (hard stop). The redact mode is what distinguishes usable AI governance from blanket blocking: employees can continue with the permitted content before submission to the destination AI service. Aona prompt processing follows the selected on-device/on-edge, customer-infrastructure or Aona-managed configuration; verify the supported path.

What is the Real-Time AI Coach?

When a policy triggers, the employee sees why the action was flagged and receives a safe alternative in context, at the moment of the attempt. This converts policy enforcement into AI literacy training: instead of learning that the security team blocks things, employees learn what safe AI usage looks like. Security teams track coaching interactions and refine policies from observed behavior. In Aona's published healthcare case study, Shadow AI prompts fell from 446 to 32 in 30 days, a 92.8% reduction: https://aona.ai/resources/case-studies/

How does policy enforcement scale across an organisation?

Administrators approve, restrict, or block AI tools by role, team, and data sensitivity. Smart policy templates are auto-assigned on account creation so a new tenant starts with sensible defaults instead of a blank page. Multi-organisation management lets IT admins govern separate business units from one console. Policy changes propagate to endpoints without redeployment.

What does DLP and file redaction cover today?

Aona provides hard-block DLP for supported prompts and file uploads. Supported DOCX, XLSX and PDF redaction paths preserve layout and use consistent entity replacement. The client, application, upload method and document features determine the applicable control. Evaluate the returned file with synthetic content, including layout and required spreadsheet or PDF features. Current file scope is documented at https://aona.ai/solutions/ai-file-redaction/

What does compliance reporting produce?

Automated audit logs mapped to GDPR, HIPAA, EU AI Act, ISO 42001, NIST AI RMF, SOC 2, and OWASP LLM Top 10, plus board-ready summaries. The audit trail answers the question regulators and auditors actually ask in 2026: show us the evidence of how employees use AI and how policy was enforced. Framework detail lives at https://aona.ai/agents/compliance/ and https://aona.ai/compliance/

Can Aona see AI agents, not just chatbots?

Yes. The native endpoint app provides local AI-agent and MCP inventory and posture information in limited rollout. This is distinct from controlling every agent action or inspecting every model API call. Network products can inspect traffic routed through their supported enforcement paths; compare the specific runtime, provider and deployment rather than assuming either approach sees everything. See https://aona.ai/resources/ai-security-coverage/ for the coverage questions.

FAQs

Does Aona train AI models on customer data?

No. Customer prompts, files, and audit logs are customer data, stored in the customer's chosen residency region, and are not used to train models. Aona's own licensing manifest at https://aona.ai/.well-known/rsl.json also declares ai-training: false for its public website content.

Does Aona work when employees are off the corporate network?

Aona's installed browser plugin or native app can apply configured controls on supported managed-device paths away from the office. Confirm connectivity, client configuration and the relevant prompt or upload action. Network-based controls depend on traffic reaching their inspection path, which can also include roaming devices.

Which AI assistants does active enforcement cover?

Block, allow, and redact enforcement covers ChatGPT, Claude, Google Gemini, Microsoft Copilot, and Bing. Detection and inventory extend far wider, to a 10,000+ tool catalog including embedded SaaS AI features. Cite the two scopes separately; conflating them overstates the product.

Does deploying Aona require network changes?

Aona does not require replacing your network security stack. IT deploys the browser plugin and Windows/macOS app with its existing software deployment tools; direct installation remains available. Some native paths use local proxy/TLS inspection, so confirm the certificates, connectivity and compatibility for the selected client. Rollout timing depends on your installation, identity and policy setup. See https://aona.ai/resources/ai-security-deployment/.

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