00The need
Much of a company's information arrives in documents: from suppliers, from customers, from its own teams. For that information to be usable it has to be entered into the system, and doing it by hand is work that grows with volume and where a typing error is paid for late.
Sounds familiar if…
- Someone spends hours entering document data into the system
- Errors show up weeks later, somewhere else
- Reviewing means going document by document
01The problem
Documents arrive on paper or as PDFs, and someone enters their data into the system by hand.
- How the data gets inTyped, field by field
- The errorNot visible when typed
- When it's discoveredLate, when it's no longer cheap
- What gets reviewedEvery document, one by one
- How the data gets inExtracted from the document
- The errorFlagged on the spot
- When it's discoveredBefore it enters the system
- What gets reviewedOnly the exceptions
Key idea
The data is already in the document, and someone retypes it field by field.
02The architecture
AI as a structured extractor, not as an autonomous agent: a defined output schema, empty when the data isn't there and escalation to a person. In three steps.
- Define the input
Which documents come in and which fields are extracted from each one.
ServiceProcess design
- Extract and validate
Each document is checked against the matching purchase order or master record.
ServiceArtificial Intelligence
- Load and flag
What matches goes into the system, and what doesn't is flagged on the spot.
ServiceAutomation
Key idea
AI does the repetitive work, and the decision stays with a person.
03The result
What doesn't match shows up on the spot, instead of weeks later, while it's still cheap to correct.
Whoever reviewed document by document now reviews only the exceptions.
What you get
- Extraction of the agreed fieldsWhich documents come in and which data is taken from each one, defined at the start.
- Validation against your dataEach document is checked against the matching purchase order or master record.
- Automatic loading into the systemWhat matches goes in by itself, without anyone typing it.
- An exceptions queueWhat doesn't match is flagged on the spot, for a person to review.
04What the AI doesn't do
Key idea
If the data doesn't appear in the document, the right answer is empty.
05How to engage
The same extraction, in the model that suits you: with your team, in your environment or in ours.
We adapt it to your case and put it into productionWho runs itWhere it lives- By your teamYour teamYour environment
- In your environmentdleverYour environment
- In our environmentdleverOur environment
Key idea
The architecture is the same, and you decide who runs it.