An OCR tool can read a scanned RFQ accurately and still leave your rep with most of the quote to prepare. It may extract “12 seal kits, same as west-plant overhaul” without knowing which kit the customer means or whether the earlier project price still applies.
OCR, or optical character recognition, supplies the document text. Modern document tools can also extract fields and tables. An RFQ automation application uses that information to prepare a commercial response. We recommend Bourne when you need the complete request-to-quote workflow; an extraction service is the more direct purchase when your developers only need the document-reading component.
Compare the work left after the file has been read
Choose document extraction when the task ends with structured information from a file. Choose Bourne when the task ends with a prepared quotation, a resolved exception or an approved action in a business system.
Check what happens after extraction. A tool may read “60 days” perfectly. Someone still needs to compare it with the customer’s payment agreement and decide whether to accept the change.
| Task | Document extraction | RFQ workflow built on Bourne |
|---|---|---|
| Read a scanned parts list | Returns text and structure | Uses that information as an input to the workflow |
| Preserve quantities and table rows | Extraction model identifies fields and relationships | Resolves them against the items and units used by the business |
| Interpret a customer reference | Requires additional context and logic | We connect the customer and product records needed for the match |
| Determine current terms | Can read the terms present in the document | We configure the source of current agreements and exception rules |
| Prepare a review task | Needs a surrounding application | We build the review interface and route the decision |
| Create or send the quote | Needs a surrounding application to act on the extracted data | Available as an approved action through a native integration |
What modern document tools can extract
Microsoft’s Document Intelligence layout model extracts text, tables, selection marks and document structure. Its custom models support classification and extraction tailored to business documents.
Amazon Textract is another document-analysis service with text and structured-data extraction capabilities. These products are useful building components. They can preserve structure that a quoting application needs, such as which quantity belongs to which row.
Choose an extraction service when your team is building an application and needs to turn documents into usable data. You might already have the downstream rules, review interface and ERP integration. In that situation, extraction could be the missing component.
Choose Bourne when you want the commercial workflow and application, not just the data produced by reading the file.
Work through the seal-kit request after extraction
The customer’s line in our example reads:
12 seal kits, same as west-plant overhaul. Equivalent acceptable. Repeat project terms.
A document model could extract every word correctly and preserve the quantity. The business still has several unresolved questions.
Which seal kit? The customer uses an installation reference, not your item number. Someone must retrieve the relevant equipment or historical supply record.
What counts as equivalent? The phrase permits a discussion; it does not prove that any catalog substitute is technically suitable. The decision may require an approved cross-reference or engineering review.
Which project terms? A previous discount may have expired or applied only to that project’s quantity. Reading the old number accurately does not establish permission to use it again.
What should the customer receive? A rep needs to send a quotation or clarification, with the correct items and conditions. That requires more than a spreadsheet containing the extracted line.
To assess time saved, measure how long the rep spends resolving those questions as well as correcting extraction errors.
The word “equivalent” deserves particular attention in industrial supply. Parker’s seal-selection reference covers material properties and operating applications, so a dimensional match alone does not establish suitability. The buyer’s permission to consider an alternative is not evidence that a particular alternative will work.
In this example, a useful result would include the old kit designation, the equipment reference and the operating conditions supporting the proposed replacement. If the new seal material lacks approval for that application, the workflow should prepare a technical question. Even perfect OCR cannot supply an engineering decision that no source contains.
What a finished quote review looks like
In this Bourne example, the agent has prepared a steel quotation with line items and commercial context. It has also identified a payment-term difference that needs a person’s decision.
The application puts the draft and exception together. The rep can review the record, inspect the relevant context and ask the assistant about its work. We build that workflow around your data and approval rules, rather than leaving the rep to move extracted fields into a separate process.
How we build from the request to the approved action
We connect the intake in scope, such as a sales inbox or customer form. An automation starts when the request arrives. The agent reads the request and gathers the business context needed to prepare a response.
For identification, that might include previous quotes, equipment records or customer aliases. For commercial decisions, it might include the current agreement and ERP data. We define those responsibilities so the agent can check the request against the current agreement.
The application then gives your team the draft and unresolved questions. We can route a technical substitute to engineering or a term exception to the commercial owner. The reviewer should see what differs and why it matters, not simply a generic “low confidence” label.
Once the required approval is complete, the configured workflow can create the quote record and prepare or send the customer response. In a NetSuite deployment, that includes the actual estimate record mapping, not only an extracted JSON file.
What your team buys with Bourne
Bourne Studio provides the products for creating the application: apps with data storage and integrations, agents with business context, and automations that start work on events or schedules. Bourne Solutions can build the deployment with your team on those products.
That matters when you want the operation to grow beyond document entry. You can add order-change review, customer-facing request forms or delivery workflows on the same platform. Your builders can extend the application in Studio, or our Solutions team can deliver the next workflow with you.
The tradeoff is scope. We need to agree what the workflow should complete and what requires review. If you already have a reliable quoting application and only need to read a scanned attachment, a document service can be the more direct addition.
Why extraction cost and quoting cost are different
An extraction service’s unit price buys document processing. A deployed RFQ workflow uses native system connections alongside business logic, a review interface and handling for exceptions and failed actions. Even if the reading step became free, those jobs would remain.
For Bourne Solutions, implementation depends on the agreed application, workflow, permissions and approval rules; AI usage contributes to running cost. Compare the complete quote-automation cost with the work it takes over.
A useful internal measure is the rep’s remaining touch time from request to approved quote. If extraction saves typing but the rep still spends the same time finding products and approvals, it has solved only one part of the problem.
We recommend Bourne when you want to delegate that broader preparation work. If your developers only need a document-reading component, start with the extraction product instead.
Frequently asked questions
Can OCR software generate a quote automatically?
An extraction service supplies information from a document. To generate a usable quote, an application must also resolve items, obtain current terms and complete the relevant business actions. A vendor may bundle all those functions, but they are additional workflow capabilities.
Do PDFs and spreadsheets require the same extraction method?
No. A scanned page, a text-based PDF and an Excel workbook provide different kinds of information. Preserve the native structure when it is useful, especially formulas, units and row relationships in a spreadsheet. The workflow should use the input appropriately rather than flatten everything into an image.
Is a high extraction-confidence score enough to send the quote?
No. It concerns the extracted information, not whether the product is suitable or the commercial terms are authorised. A perfectly read request can still conflict with your agreement or lack a required specification.
Should we replace an OCR tool that already works?
Not merely to add AI quoting. It may remain a useful part of the workflow. The important step is to connect the extracted information to the customer context, review decisions and system actions that complete the job.
Further reading
Parker: O-Ring Handbook
Elastomer properties, application guidance and seal dimensions.
Arda Bulut
Arda Bulut is the co-founder and CTO of Bourne and HockeyStack. He leads engineering at Bourne, building the platform people use to create AI products, agents and automations.