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How Endpoint Care works

Every user IT request follows the same lifecycle:
  1. Understand - the employee types a request (or clicks a quick action). The agent interprets the intent and selects the matching skill. If nothing matches, the run becomes a triage run.
  2. Plan - the agent reads the skill and produces an explicit, ordered plan of tool calls for this specific goal.
  3. Check - the plan passes through the guardrail pipeline: intent screening, plan validation against the skill’s allowed tools, and central policy evaluation.
  4. Execute - steps run one at a time on the device. Diagnostic steps are read-only. Corrective steps pause at gates: a preview of exactly what will change, and a consent prompt the user must approve.
  5. Verify and report - the agent confirms the outcome (including asking the user), then produces a summary. Every run, resolved or not, is recorded as a ticket with the full diagnostic trail.

Major components

  • Desktop agent - the app is on each computer: chat UI, local diagnostics and fixes, enforced guardrails. Installs with one command.
  • Skills - natural-language playbooks, one per problem type (disk cleanup, email repair, VPN). Each defines its steps and allowed tools. IT can add custom skills and toggle any skill from the cloud.
  • Tools - deterministic, code-reviewed functions that do the actual work (scan disk, flush DNS, repair keychain). The AI chooses which to use; it never runs raw commands.
  • Guardrails - the checks between request and action: intent screening, plan validation, policy, and per-step consent and previews. Enforced by the system, not the model.
  • Triage - the safety net. Unresolvable issues are diagnosed, categorized, and routed with evidence. No request dead-ends.
  • Cloud console - central skill management, policy, analytics, and audit.
  • Integrations - ticketing systems, plus Slack and Teams entry points.

Terminology