Let any AI agent take governed actions in Guidewire

It's a real concern — and the reason Upware learns your specific Guidewire implementation, not a generic template of it. The Action Model records the actual workflow as it runs in your environment, including your custom fields, approval steps, and routing logic. When your configuration changes, you re-record the affected workflow; the rest stays intact. Because execution replays deterministically against the learned path, there's no fragile script that silently breaks on the next rule change.

Every action an agent can take is encapsulated as a governed AI skill — it cannot call the underlying system directly. Upware applies RBAC, pre-execution policy checks, and post-execution verification before and after each write. For regulated steps like claim payments or endorsement issuance, you define the approval conditions and attribution requirements at the skill level; the agent cannot bypass them. The full action log, including who authorized the run and what changed, is captured in the audit trail.

Cross-module consistency is exactly where unharnessed agents create risk, because an isolated write to one module can leave the others out of sync in ways that only surface during reconciliation. Upware models the multi-module workflow as a single governed action sequence — it knows the ordering, the cross-system checks, and the rollback conditions. If a step fails mid-flow, the skill surfaces the failure with enough context to resolve it rather than committing a partial update that corrupts the record across modules.