Turn requests into checked records

AI Data Extraction and Business Record Automation

BusinessForward turns emails, documents, notes, and messages into structured business data. The workflow can understand the request, match it to existing records, check for missing information, and prepare the right action for review. This page is about records that arrive as text — emails, documents, and notes. If your requests start as speech in the field, start with Custom Voice AI.

Example workflow

“Send 50 feet of two-inch PVC to Jobsite B.”
Understood

Material request

The workflow identifies the requested material, amount, unit, and destination.

Matched and checked

Business records

Jobsite B and the material description are matched to existing records. Availability and missing details are checked.

Ready for review

Proposed action

The workflow prepares the right next step — a transfer, an order, or another action required by the request and business rules. A person reviews uncertainty.

More than copying text

Extraction is only the first step.

A useful workflow must understand the request and connect it to real business records. It should check missing details before it prepares a record or action.

The exact design depends on the source data and the access available in the existing software.

Manufacturing coordinator checking a work order against parts stored in warehouse bins.
A warehouse coordinator checks a work order against physical inventory.

A checked path

Move from a free-form request to a useful next step.

  1. 1. UnderstandIdentify the requested work.
  2. 2. MatchFind the correct project, item, location, or customer.
  3. 3. CheckConfirm quantity, unit, availability, and required details.
  4. 4. PrepareCreate the supported record or action for review.
  5. 5. ReviewSend missing or uncertain information to a person.

Active development

Email and document extraction are work in progress.

BusinessForward is actively developing email and document extraction into structured records. The example above shows that active direction.

The email and document features on this page are new work. We are building them now on the same approach that already runs in QR Inventory, and no customer is running them yet.

Production experience

QR Inventory already applies these AI skills to voice requests.

In QR Inventory, users can make spoken requests, match them to existing records, check inventory, and receive an explanation of the result. Users can also ask how to complete a task or follow guided setup and transaction steps.

Optional technical detail

Match everyday words to the records the business uses.

Read how record matching works

Record matching means matching an informal description to the correct existing record. A technical term for this is entity resolution. For example, “two-inch PVC” must point to the right material record, unit, and available quantity.

When more than one record may fit, the workflow should ask for help or send the choice to a person.

Laboratory technician checking sample vials against a paper record and tablet.
A lab technician checks sample information before recording the result.

Choose the right level of help

When the format never changes, a simple fixed rule is enough.

Use a standard parser

Choose a parser — software that reads a fixed format the same way every time — when the source always follows the same clear format and no record matching is needed.

Add a focused AI workflow

Use AI when wording varies and the request must be matched to existing business records.

Keep a person in control

Require review when information is missing, a match is uncertain, or the resulting action carries risk.

Questions business owners ask

Check the source, records, and review rules.

Can AI understand free-form emails and messages?

BusinessForward is actively developing this work. The result depends on the source, the wording, and access to the business records used for checking.

Can extracted information be checked against our existing records?

Yes. The workflow is designed to understand the request, match it to existing records, and check required details before preparing an action.

What happens when a request is incomplete?

The workflow should identify the missing information and stop for a question or human review instead of guessing.

Can employees approve a record before it is created?

Yes. A review step can be required before a supported record or action is created.

When is a standard email parser enough?

A standard parser may be enough when messages follow one stable format and the values do not need uncertain record matching.

Can the workflow process attachments?

Yes. We can work with message text and supported attachments, such as PDF and spreadsheet files. During the review we confirm the formats your senders actually use. This feature is new work. We are building it on the same approach that already runs in QR Inventory; no customer is running it yet.

Can it create or update records in existing software?

That depends on the access the software provides and the review rules the workflow needs. We confirm those limits before choosing an approach.

Start with a real input

What information does your team still read and enter by hand?

Show us the source, the records used to check it, and the action employees take next.