Service agent
Find context, summarise a case and propose the next service step.
Connect focused agents to permitted customer operations, knowledge and business tools, with clear read, draft and approval-required action tiers.

Each capability stays connected to customer context, ownership and the rest of the platform.
Find context, summarise a case and propose the next service step.
Analyse campaign performance and prepare an approved draft or recommendation.
Review process state, exceptions and work that needs attention.
Use permitted development knowledge and connected tools for focused tasks.
Separate read-only, draft and approval-required actions.
Measure quality and keep supported actions attributable and reviewable.
Choose one role, outcome, user group and approved source set.
Add only the systems and permissions required for that outcome.
Test answers and proposed actions against real operating scenarios.
Release incrementally with logging, review and human escalation.
CRM, Slack, Teams, GitHub, Jira, email, ERP and knowledge sources should appear as available only after the integration path is confirmed.
Explore the integration approachDirect answers, with availability and integration dependencies kept explicit.
An AI agent is a focused system that can use permitted data and tools to answer, draft, recommend or perform an approved action for a defined business role.
They can where the connector and permission path support the action, with approval required for sensitive changes.
Only the connected and permitted sources defined for its role and the current user.
Through least-privilege access, separate action tiers, approval gates, logging, evaluation and human escalation.
Use a focused Discovery Workshop to map systems, users, data, workflows, deployment and the first measurable release.