Governance and compliance

Your AI answers confidently. Make sure it answers from approved knowledge.

Named owners approve what agents may use. Each agent reads only the knowledge its job needs. Every read is recorded, with the person or API key, the document and the time.
Read the governance frame →
Research preprint
3×

fewer input tokens than keyword search (BM25), in a stale-version test

Govern your context when it's written, and you stop paying to search through it every time you ask. Accuracy goes up and cost goes down.

97%

answer pass rate, against 90–93% for BM25 (preprint, not peer reviewed, small corpus)

Same context, every time

the same documents for the same question

Research withEmory University, Goizueta Business SchoolIBM Research
Read the preprint →
Role-based access control

Decide who can build, view and use AI.

Platform roles

Identity and admins
Every plan includes Google sign-in. OIDC single sign-on with Entra ID, Okta or Google Workspace comes with Enterprise. Admins manage users, billing, security settings and organization configuration.
Editors
Create and manage agents, data sources and tools. Configure prompts and workflows.
Users
Use published agents. No access to build tools, configuration or other users' data.

Resource permissions

Granular access
Control access to agents, data sources, conversations and analytics separately.
Team isolation
Scope data and analytics by team. Sales can't see HR's conversations, and Marketing can't open Finance's documents.
Sales team permissionsExample
AgentsEditor
Data sourcesViewer
ConversationsNone
Audit trail

Every action has a name and a time on it.

Logins, document uploads, agent changes and configuration updates are all logged with who did them. The trail is append-only and kept for as long as your policy says.
10:42:01user@acme.comCREATEDagent_sales_v1
10:45:15admin@acme.comMODIFIEDpolicy_doc.pdf
11:02:33guest@acme.comDENIEDrestricted_view
11:15:07ops@acme.comEXPORTEDq3_report_data
Sample data
Can you analyze the Q3 comp package for Alex Smith?
PII_DETECTED
I can use the anonymized salary bands, but I can't process individual compensation data under your privacy controls.
POLICY_COMPLIANT · GUARDRAIL_ACTIVE
Sample conversation
Conversation monitoring

See how AI is used across your organization.

Review conversations by team, user, agent or time period.
  • PII detection flags sensitive data before it reaches the model
  • Policy compliance checks on every response
  • Guardrails for sensitive topics and data access
Citation enforcement

Every answer comes from your documents, with the source attached.

Document grounding

Agents answer from your uploaded knowledge base: SOPs, policies and product docs.

Verifiable sources

Every response includes citations linking back to specific documents and passages. Users can check a claim with one click.

Strict source adherence

Answers stay inside your approved document set, so results are consistent and fabricated answers drop sharply. Every claim points to a source someone can check.

Model governance

Choose the models, the routing and the budget.

Model switching

Switch between ChatGPT, Claude, Gemini and open-source models mid-conversation, without losing context.

Smart routing

Prompt routing weighs complexity and cost to pick a model. Optimize for speed, quality or price per query.

Cost controls

Track spend by token, team or department. Set budgets and alerts.

Analytics and cost

Know what AI costs, team by team.

Organization-wide visibility into AI usage, adoption and spend.
  • Token usage by user, team and agent
  • Cost dashboards with department breakdowns
  • Adoption: active users, conversation volume and agent usage
  • Budget alerts and spend limits per team or project
45k
Daily tokens
$124
Cost this month
89%
Adoption
12
Active agents
Sample data

Deploy enterprise AI with guardrails.

Start with governance built in from day one, so compliance never has to be retrofitted.

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