Aberrant AI

Use case

Purchase Approval Workflow

Approvals vary by person, amount, location, and vendor without a clear system.

Workflow model

Normal workflow first. AI assistance only when the path breaks.

Normal workflow

Requests route by amount, vendor, location, role, and approval rules with a decision record.

Where the workflow breaks

A purchase sits between thresholds or needs context that the rule table does not capture.

What AI prepares

Summarize evidence, identify the right approver, and draft the approval rationale.

What humans approve

Spend approval, vendor exception, and policy override decisions stay with humans.

What becomes a reusable rule

Repeated exceptions become clearer thresholds, routing rules, and policy notes.

Why status quo fails

Manual coordination cannot create reliable control.

Approval rules are remembered, not enforced.

Comments are scattered across chats and emails.

Purchase status is unclear to requesters.

Audit history is weak when decisions are questioned.

Workflow Layer

The workflow becomes a controlled sequence.

Route approvals by rules, capture comments, notify owners, and preserve audit trails.

Request submitted
Rules applied
Approver notified
Decision captured
Requester updated
Audit trail stored

Core features

What the system needs to do.

Approval matrix

Amount thresholds

Comment capture

Notifications

Audit trail

Exception dashboard

Connected tools

Tools that can participate in the flow.

Custom workflow appERPEmailSlackTeamsDashboards

Expected outcome

Faster approvals with stronger control.

01

Implementation

Map request types

02

Implementation

Define approval rules

03

Implementation

Build decision and notification flow

04

Implementation

Test exception cases

Next action

Design Approval Logic

Tell us where this workflow currently breaks. We will map the AI assistance, approval gates, and first build path.