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Readiness stays explicit
Knowledge, routing, Actions, and policy requirements are reviewed before activation.
Set clear boundaries for AI support across knowledge, Actions, teams, and outcomes.
AI customer support for large organizations
Give each Workspace an explicit readiness path, keep sensitive work behind Risk Policy, and measure outcomes with definitions your organization can inspect.
Start with 100 creditsOne-time $1 activation · 100 credits included · No automatic subscription
How it works
Move from isolated automation to an accountable support system.
Readiness, permission, and measurement remain explicit before an Agent represents the organization at scale.
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01 · Govern
Define the knowledge and policy boundary
Scope sources, Members, Agent behavior, and required handoff rules inside each Workspace.
Readiness
Review requiredKnowledge
Ready
Risk Policy
Approved
Handoff route
Configured
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02 · Control
Keep sensitive Actions behind explicit approval
Separate safe lookups from work that requires customer confirmation or Member approval.
Risk Policy
EnforcedAccount lookup
Proceed
Refund request
Member approval
Unknown result
Do not retry
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03 · Measure
Review outcomes with enough context to trust the number
Keep metric definition, Data as of time, Agent, channel, and team context available beside the report.
Outcome report
Data as of 14:30Definition
Verified Resolution
Freshness
Visible
Owner
Support operations
Every Agent operates inside a visible boundary. Every outcome keeps the evidence behind it.
What changes
Control that remains understandable across teams.
The organization can scale support automation without hiding who approved the knowledge, the Action, or the outcome definition.
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Sensitive work stays governed
Risk Policy decides when the Agent may proceed, must request review, or must hand off.
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Outcome reporting stays inspectable
Metric definitions and Data as of time remain visible beside the number.
Designed for the edge cases
Enterprise controls built into the support workflow.
Governance works best when it sits beside the decision instead of in a document no one sees during the Conversation.
Workspace boundaries
Keep Agents, Members, sources, Conversations, and billing inside an explicit operating boundary.
You stop dealing with: using tags as the only separation between business units or customer groups.
Readiness requirements
Review knowledge, evaluation, Action, routing, and security state before an Agent becomes active.
You stop dealing with: launching from a configuration checklist stored outside the product.
Risk Policy and approval
Require customer confirmation or Member approval when the Action risk demands it.
You stop dealing with: treating a prompt instruction as the authorization boundary.
Defined outcome analytics
Track measures with versioned definitions, event time scope, freshness, and an owner.
You stop dealing with: comparing dashboards that use different meanings for the same label.
Accountability in the product
Policy stays close to the decision it governs.
Members can see why the Agent answered, acted, paused, or handed off without reconstructing the logic from separate systems.
Source
The answer keeps its evidence
Members can inspect the source and revision supporting the response.
Decision
The Action keeps its policy state
Approval reasons and parameters remain tied to the request.
Outcome
The report keeps its definition
Freshness and measure meaning remain visible beside the result.
Choose the governance model
Operational controls inside the Conversation, not around it.
Compare how each approach handles boundary, approval, evidence, and outcome measurement.
Workspace boundary
CommunicateProduct enforced
Generic AI botAccount dependent
Custom platformYou design it
Action approval
CommunicateRisk Policy
Generic AI botPrompt or flow
Custom platformYou build it
Outcome definition
CommunicateVersioned contract
Generic AI botVendor metric
Custom platformYou govern it
Human takeover
CommunicateSame Conversation
Generic AI botTransfer flow
Custom platformYou integrate it
Questions before you start
Questions enterprise teams ask about control.
How governance, approval, evidence, and reporting work together.
Make the boundary visible before the Agent goes live.
Choose one Workspace, connect its approved knowledge, define the Risk Policy, and review the outcome you need to measure.
Start with 100 creditsOne-time $1 activation · Grounded answers · Human takeover · Cancel anytime