Asgard AI vs native AI connectors
A native connector plugs your AI client straight into a system by giving the agent a credential. It's quick — but the agent now holds a secret, with whatever access that secret carries. Asgard AI keeps the convenience and removes that risk by brokering the call.
The fundamental difference
With a direct connector, the secret moves to the agent. With Asgard AI, the secret stays in the vault and only the result comes back. The agent gets a capability, not a credential — so a leaked prompt, log or model provider can't turn into a leaked key.
| Native connector | Asgard AI | |
|---|---|---|
| Where the credential lives | Given to the agent | Encrypted in the vault, never returned |
| Scope of access | Whatever the credential allows | Scoped per agent, per operation, per parameter |
| Audit trail | Partial / provider-dependent | Every action logged & attributable |
| Content safety (DLP, injection) | Not built in | Scanned and redacted in and out |
| Human-in-the-loop | Rare | Approvals on sensitive actions |
| Stop a misbehaving agent | Rotate the secret everywhere | One-click kill-switch + auto-quarantine |
| Which clients can connect | Whoever has the secret | You choose the allowed clients |
| Governance evidence (e.g. ISO 42001) | Hard to produce | Ready as audit evidence |
"But a firewall already inspects agent traffic"
Traffic-inspection tools sit beside the agent and watch what it does — useful, and Asgard AI overlaps there with its guardrails. But inspection alone still assumes the agent holds the keys. Asgard AI is the access broker: it holds the keys, so it can stop an action before it happens, not just observe it.
When a native connector is fine
For a throwaway experiment against a non-sensitive, read-only sandbox, a direct connector is quick and reasonable. The moment real credentials, production systems or customer data are involved — or you need to prove control — brokering through Asgard AI is the safer default.