Aberrant AI

Use case

Client Document Collection

Teams repeatedly chase the same files across email and chat threads.

Workflow model

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

Normal workflow

Requests, reminders, file receipt, status updates, and owner notifications run from a checklist.

Where the workflow breaks

The client sends an unclear file, misses a document, or replies outside the expected channel.

What AI prepares

Classify the reply, draft the follow-up, and flag what remains blocked.

What humans approve

Final acceptance of ambiguous documents or client-sensitive messaging needs review.

What becomes a reusable rule

Repeated document gaps improve checklist wording, reminders, and client-specific rules.

Why status quo fails

Manual coordination cannot create reliable control.

Document requests are buried in threads.

Teams ask for the same file repeatedly.

Client status is unclear without manual checking.

Received files are not tied to a workflow stage.

Workflow Layer

The workflow becomes a controlled sequence.

Create request lists, reminders, status tracking, owner visibility, and completion trails.

Request created
Checklist sent
Reminder scheduled
File received
Status updated
Owner notified

Core features

What the system needs to do.

Document checklist

Client reminders

Status dashboard

Owner assignment

Completion trail

Connected tools

Tools that can participate in the flow.

GmailOutlookWhatsAppGoogle DriveMicrosoft 365Custom portal

Expected outcome

Fewer follow-ups and cleaner client accountability.

01

Implementation

List recurring documents

02

Implementation

Define owners and due dates

03

Implementation

Build request and reminder flow

04

Implementation

Test client-facing messages

Next action

Fix Document Collection

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