What gets built
- Document reading and field extraction
- Approval rules, alerts, and hand-offs
- Answers grounded in internal documents
- Connections to authorized email, messaging, and systems
Guide controls and deliverables
- A workflow map and named owners
- Documented validation fields and rules
- A record of each run and exception
Operational signs to review
- The team loses hours reading, sorting and copying data across email, chats and spreadsheets
- Approvals stall because someone has to chase every task and remember every step
- Manual errors create corrections and delays that require review
How AI automation works
Capture
The workflow receives what arrives today by email, WhatsApp, forms or folders: PDFs, photos, messages or spreadsheet rows. The input channel doesn't need to change.
Understanding
A language model reads each input and extracts what matters (who, what, how much, when) in a fixed format the system can validate field by field.
Rules and action
With the extracted data, explicit business rules decide the next step: approve, ask for a missing item, notify someone or register it in the system. Anything ambiguous goes to a person.
Logging and review
Every step is logged. Inputs that do not complete a rule are reviewed periodically to prioritize adjustments and define exceptions.
Workflow description
Before
The team loses hours reading, sorting and copying data across email, chats and spreadsheets
After
The workflow receives a request management request, extracts defined data, validates required fields, and records or hands it off according to the agreed rule.
Extracted fields, applied rule, exception owner, and a record of the run.
What the company needs before starting
- One concrete process with an owner who knows it end to end
- Access to the channels where work arrives: email, WhatsApp, forms or folders
- Test documents or messages covering usual inputs and exceptions
- A clear rule on what the system may decide alone and what a person reviews
Common automation mistakes
Automating a process nobody has defined
If everyone does it differently, define the flow on one page first; then automate it.
Starting with the most complex workflow
Start with a bounded, repetitive, lower-risk workflow before touching a critical one.
Letting the model decide without rules
AI reads and proposes; business rules decide. Without that separation there is no traceability.
Not defining review
Without a rule for reviewing exceptions, the workflow has no clear owner when information is missing.
What to review during operation
- request management inputs processed and handed off
- Exceptions by rule
- Fields rejected by validation
- Records pending review
Terms worth knowing
- Data extraction
- Turning free text (a PDF, a message) into fixed-format fields a system can validate.
- Human-in-the-loop
- A design where a person reviews or approves inputs the system flags as uncertain.
- Webhook
- An automatic notice one tool sends to another when something happens, with nobody copying data.
- Traceability
- A record of every step, data point and decision in the flow, to know what happened and why.