01 · Batched in the right order.
Update sets are grouped into a release and sequenced by dependency — so nothing lands before what it needs.
Batch multiple changes, sequence every update set in the right order, and promote across instances from one canvas — with conflicts surfaced before you release. All driven from chat.
Release the warranty claim change to acme-test — check for conflicts first.@ for records · / for commands
Sequence every update set, batch multiple changes, and promote across instances from one canvas — in the right order, with conflicts surfaced before you release. All driven from chat.
Group related changes into a batch and Phyllis works out the order they have to ship in — respecting dependencies between update sets so nothing lands before the thing it relies on. One batch, sequenced, ready to promote.
Before anything reaches your next instance, Phyllis checks the batch for collisions, missing dependencies and records newer on the target — then she holds or resequences so you promote knowing exactly what will land, and what won't.
Nothing promotes blind. Phyllis previews the update set against the target, scans for conflicts and missing dependencies, and stages a rollback path — every promotion waits on your approval, so a bad change never reaches production unseen.
Update sets are grouped into a release and sequenced by dependency — so nothing lands before what it needs.
Preview conflicts are found and resolved, and the release versions are checked on the target before anything moves.
Approve in chat and watch a live progress card. Production is promoted from your Deployments page.
Phyllis releases to test and UAT from chat. Production is promoted from your Deployments page, under your change process — by design.
Sequence and batch update sets, surface conflicts before they bite, and promote across instances in the right order — all driven from chat.
Phyllis builds and extends complete custom applications — any data model, automation or access model — grounded in your live instance and staged for your approval.
Read the use caseCase types, health scoring, success plays, risk definitions — the full customer success framework, built and staged.
Read the use casePhyllis builds and extends your entire integration layer — any connection, credential or retry rule — grounded in your live instance and staged for your approval.
Read the use caseNot from chat. Phyllis releases to test and UAT from chat, on your approval. Production is promoted from your Deployments page under your change process.
Preview conflicts are surfaced and resolved before the release moves, and the release versions are checked on the target.
By dependency — Phyllis sequences the batch so nothing lands before what it needs.
Yes. Every release shows its progress live, and approvals are recorded in the audit log.
One teammate from the first question to a promoted, tested change.
Phyllis grounds herself in the full context of your ServiceNow instance — its tables, ACLs, flows, update sets, configurations, and dependencies. Every answer is evidence-backed and traceable to the records it came from.
Explore AnalyzeSay “I want to implement ITSM” and Phyllis returns sequenced stories with priorities, points, and acceptance criteria — synced both ways with Jira or ServiceNow Agile 2.0.
Explore PlanPhyllis develops on the platform — from tables, business rules, flows, and ACLs to the records behind them — then verifies and tests every change.
Explore Develop
