AI Security Operations
AI that accelerates the work without training on your data.
What this replaces
Security teams drown in findings that each need context, a fix, and an explanation for three different audiences — work that is exactly what language models are good at, if the data governance is right.
What Offload does
AI assistance woven through the platform: suggested fixes on findings, scan and report summaries, a platform-aware chat assistant, and security-questionnaire automation — all using the customer's own model-provider API keys.
What you get
- Suggested fixes for individual findings, with the finding's code context
- AI summaries on scan reports across cloud, code, container, and Kubernetes scans
- Platform-aware chat assistant grounded in your posture data
- Security-questionnaire auto-answering from an approved knowledge base with evidence linkage
- Bring-your-own provider: Anthropic, OpenAI, or Google — your keys, encrypted at rest
- No training on customer data; AI responses with customer context are never cached across tenants
How it works
AI features run only when invoked, send the minimum context needed (a finding and its excerpt — never a repository), and call the provider configured by the customer directly over TLS.
The response cache is hard-gated to generic, tenant-agnostic content — customer-specific answers are never stored or shared.
One platform, one risk view
AI operates on the platform's unified data — the same finding a human triages is the one the model explains, fixes, and reports on.