See your kind of NetSuite problem solved live.
A 45-minute working session: how the configuration graph is built, how dependencies are traced, and how a business request becomes a governed change set that is tested in Sandbox before anyone approves it.
Tell us what you would want to ask your NetSuite.
We will tailor the session to your environment and the questions your team currently cannot answer.
- How ConfigLedger builds a configuration graph of a real account.
- Dependency tracing on a field, workflow or saved search.
- A natural-language change request turned into a change plan.
- Sandbox build, automated QA and before/after review.
- Governance: execution levels, approvals and rollback readiness.
- How access is granted, scoped and revoked.
Questions we are usually asked first.
No. Natural language is how you talk to it, not what it is. Underneath sits a persistent configuration graph of your account and a change engine that plans, builds, tests and records changes as governed change sets.
It can, within the limits you set. ConfigLedger runs at one of three levels: read-only analysis, Sandbox agent (build and test only), or production agent where approved change sets may be promoted under your governance rules.
Only if you explicitly configure that. The default posture is that Production changes require named human approval, with additional approvals available for financial controls, scripts and integrations.
We do not claim that. Many configuration changes can be restored from a captured snapshot or a corrective deployment, but some operations — merged records, deletions, data already sent to an external system — cannot simply be undone. ConfigLedger produces a rollback plan and a rollback confidence rating before it executes anything.
Oracle's assistant helps a developer generate SuiteScript and custom objects inside their IDE. ConfigLedger is aimed at the business lifecycle around a change: understanding the existing environment, tracing dependencies, planning, testing against the requirement, collecting approvals, deploying and monitoring.
From the configuration graph built from your own account — the fields, workflows, scripts, searches, roles, forms, segments and integrations that exist, and the relationships between them. The AI explains and plans against that graph rather than inventing dependencies.
Depending on your NetSuite configuration and the permissions granted, areas such as saved searches, custom fields, workflows, custom segments, roles, scripts, custom records and related configuration metadata.
No. It removes repetitive discovery and manual investigation so internal teams and partners can spend time on architecture, process and judgement.
It can show detected dependencies and flag potential risk, described cautiously. Removal should still follow your own testing, review and change-control processes.
That is deliberately an implementation detail. The value is the NetSuite configuration graph, the change orchestration, the testing framework and the governance — the underlying model is replaceable infrastructure.