AI Data Security - Data-Loss Prevention for Agents
An agent that can read your data can leak it. Agentshield classifies sensitive data in agent traffic and blocks it from leaving to anywhere you did not authorize.
Direct answer
AI data security for agents means controlling what sensitive data an agent can access and where that data can go. Agentshield applies data-loss prevention in the agent action path: it classifies PII, secrets, and confidential content in real time, and blocks any attempt to send it to an unauthorized destination, such as an external email, a paste site, or an off-allowlist API. Egress is checked against policy, so a prompt-injected agent cannot exfiltrate data even if it is tricked into trying.
Classifies in real time
PII, credentials, and confidential content are detected in the traffic the agent handles, not after it has already been sent.
Egress allowlists
Define where data may go. Sends to anywhere off the allowlist are blocked, so exfiltration to an attacker destination fails by policy.
Redaction and masking
Sensitive fields can be masked or redacted before an agent or a log ever sees the raw value, keeping secrets out of reach.
Where it is used
Data-loss prevention in the field.
LLM security
LLM security is not a model setting. It is a runtime control plane that inspects inputs, constrains actions, and records what happened, in front of every LLM app you ship.
Read more →RAG security
Your RAG pipeline retrieves untrusted documents and feeds them to the model. That is an injection vector. Secure it by inspecting retrieved content before the agent acts on it.
Read more →Coding agents
A coding agent runs commands, edits files, and calls tools with real credentials. Scope what it can touch, gate the dangerous actions, and log every move.
Read more →Customer service agents
Support agents read messages from strangers and can issue refunds and touch accounts. Inspect every message, protect customer data, and gate the actions that move money.
Read more →The rest of the plane