Your question is what reaches the model. In the governed workspace, sensitive values are tokenized before model context · meaning intact, values withheld. Credentials are scoped and never enter context. Every source touched streams to your SIEM. Enforced by architecture · not user training.
Agents take paths nobody pre-approved. The governed workspace is the checkpoint every path runs through · enforced by architecture, not by user training.
Provisioned here · inherited by every surface
Salesforcesales_read
Snowflakeanalytics_ro
Postgresapp_read
Jiraissues_readCredentials are scoped per identity, encrypted at the boundary, and revoked in real time. The model never holds a token or an API key, in local development or in production.
Secure connections# Saved once. Re-run by anyone approved.$ run "Slipped deals · Q2"→ salesforce_opportunities 18 rows→ jira_issues 64 rows✓ slipped_deals_joined 14 rows$ share result#7c21 --with revops# Reviewed in the web app · same trail.▍
Data enters a governed runtime in your cloud and raw records stay behind the boundary. Sensitive fields are tokenized before model context · meaning intact, values withheld · so agents use the signal, never the raw value.
Governed workspaceWho approved what, and when · reviewable in the console
Every tool call, source, and artifact becomes a structured event: user, tool, system, scope, redaction status · streaming to Splunk, Datadog, or your own pipeline as it happens.
Trust and governanceAgents take paths nobody pre-approved. The workspace is the checkpoint every path runs through.
Data enters a governed runtime in your cloud · raw records stay behind the boundary.
Sensitive fields tokenized, meaning intact · the model reasons without holding values.
Every tool call, source, and artifact · structured events streaming to your SIEM.
An agent segments accounts using signal derived from sensitive fields. The values themselves never reach context, and authorized users still see real data on their side.
An agent improvises a route through three systems. Each hop still runs through the same checkpoint, so the unplanned path is as governed as the planned one.
Structured events land in the SIEM your team already watches, so AI activity is reviewed with the same tooling and the same on-call as everything else.
Results, not raw records · and sensitive values are tokenized before model context, with meaning intact. Credentials are never in context at all: auth is resolved at the workspace layer and only the data the caller's scope permits is returned.
In your workspace, encrypted with your KMS keys (Enterprise) or our managed KMS (Team). For VPC deployments credentials never leave your cloud · we operate the software, you own the data plane.
Enforced. The workspace is the runtime the work happens in, so the controls are structural rather than guidance an agent could route around. Revocation takes effect immediately across every surface.
Same data gateway, same governance model. What changes is who is driving and where the work is written.
Provision access, review what agents did, and hold the controls in one place.
Read the Agent Console pageLiveConnect100+ live enterprise systems behind the same six verbs, scoped per user and agent.
Read the LiveConnect pageOne MCPOne governed tool surface that Claude, ChatGPT, Cursor, and Copilot can use.
Read the One MCP pageAdaptive ContextA knowledge map per connection: schema, business rules, and joins that already worked.
Read the Adaptive Context page
CISO one-pager · architecture diagram · controls matrix · sample SIEM events · NDA template. Everything your team needs to say yes.
