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ENUA
  1. Services
  2. /AI & Intelligent Automation
  3. /Document and inquiry processing

AI FOR INCOMING DOCUMENTS & REQUESTS

Documents and inquiries — turned into structured data.

We build AI processing for invoices, applications, emails and other incoming material. The system identifies the type, extracts relevant fields, validates them and passes the result into your workflow. Ambiguous cases go to your team for review.

Discuss document processing→Explore the processing example→

From an incoming file to a reviewed record.

Documents passing through recognition into structured fields for review.

Which incoming workload takes up your time?

Different document types need different rules. Start with one document type or workflow that can be evaluated clearly.

  • Invoices and supporting documents

    Staff manually copy references, amounts and document numbers into another system. We define the fields and validation needed before handing over a record.

  • Customer emails and inquiries

    Messages need to be read, categorized and assigned. We help prepare the category, summary and relevant details for a work queue.

  • Applications and document packs

    Information arrives across different files, with some fields missing. The system can assemble an agreed set of data and highlight what needs clarification.

FROM SOURCE TO FIELDS

See the result — and what still needs review

Choose an example. Extracted fields are tied to the source text, and missing values are not invented.

Fictional examples. No files are uploaded, recognized or sent to another system.

Incoming material

Invoice DEMO-014. Supplier: Demo Company. Amount due: 12,400 UAH. No payment due date is provided in this example.

Prepared fields

Number
DEMO-014

Found in source

Supplier
Demo Company

Found in source

Amount
12,400 UAH

Found in source

Due date
Not provided

Missing information

Next step

Clarification needed

Check the due date before sending the record to the accounting system. No payment is initiated.

Invoice

Invoice DEMO-014. Supplier: Demo Company. Amount due: 12,400 UAH. No payment due date is provided in this example.

  • Number: DEMO-014 (Found in source)
  • Supplier: Demo Company (Found in source)
  • Amount: 12,400 UAH (Found in source)
  • Due date: Not provided (Missing information)

Clarification needed

Check the due date before sending the record to the accounting system. No payment is initiated.

Inquiry

“I have not received the parcel for order DEMO-032. Could you tell me where it is?”

  • Topic: Delivery (Found in source)
  • Order: DEMO-032 (Found in source)
  • Suggested queue: Delivery support (Rule-based suggestion)
  • Parcel location: Needs a system lookup (Missing information)

Ready for operator review

Route the inquiry to the delivery team to check the status. Do not promise a date or issue a refund without the relevant information.

Extracting text is only the first step. Operational workflows also need validation, clear statuses and exception handling.

Exceptions should not disappear into the queue

After processing, the team should see what is ready, what needs clarification and why a record has not moved on.

  • Ready for the next step

    Required fields are present, formats are valid and checks have passed. The next handoff follows agreed rules.

  • Needs review

    An unclear passage, conflicting value or unfamiliar format enters a separate review queue with an explanation.

  • Processing history is available

    Source material, corrected fields and handoff outcomes can be inspected. Retrying should not create duplicate records.

Document review queue with completed records and a field requiring review.

What can be automated

The steps depend on input quality, document types and the requirements of the receiving system.

  • 01

    Intake

    Files, forms, email or an agreed integration channel, with defined format, size and duplicate-upload rules.

  • 02

    Text recognition

    Add OCR for scans and images. Test readability on representative examples, including tables and unusual layouts.

  • 03

    Classification

    Recognize agreed document types and inquiry topics. Unknown categories are not forced into an arbitrary match.

  • 04

    Field extraction

    Extract agreed fields such as references, dates, amounts, line items or request details, retaining a link to the source.

  • 05

    Validation and normalization

    Check required fields, formats and agreed business rules before writing to an operational system.

  • 06

    Routing and handoff

    Prepare a record for a CRM, ERP or operator queue, with visibility into results, retries and errors.

How we design the processing workflow

Evaluate the whole document journey, not just one recognized passage.

StageWhat we doWhat you receive
  1. 01

    01. Collect representative samples

    Review typical, difficult and incomplete inputs. Identify cases that must reach a human reviewer.

    Representative samples and cases requiring human review.
    Representative samples and cases requiring human review.
  2. 02

    02. Agree fields and rules

    Define field values, validation rules and statuses, and identify the authoritative system for reference data.

    Agreed fields, validation rules and statuses.
    Agreed fields, validation rules and statuses.
  3. 03

    03. Evaluate processing

    Test recognition, extraction and classification against a separate evaluation set. Review errors by type.

    Evaluation results and common error patterns.
    Evaluation results and common error patterns.
  4. 04

    04. Build review and handoff

    Build exception review and agreed integrations. Test corrections, retries and duplicate handling.

    A review interface and connected integrations.
    A review interface and connected integrations.
  5. 05

    05. Launch on a limited workload

    Start with agreed document types, monitor errors and add formats after evaluating them.

    Pilot processing for agreed document types.
    Pilot processing for agreed document types.

ESTIMATE

Show us what comes in and where it needs to go

For an initial discussion, anonymized examples, required fields and a description of the current manual process are useful.

Discuss document processing→

  • Formats and quality

    Which file types, languages, tables and scan quality levels occur?

  • Fields and checks

    Which values are required and how does the team check correctness?

  • Receiving system

    Where does the result go and is an API available?

  • Workload and exceptions

    How much material arrives and who reviews ambiguous cases?

QUESTIONS & ANSWERS

Questions about document processing

Turn incoming documents and inquiries into validated fields and the next workflow step. Not autonomous decision-making or simply chatting with a PDF.

Questions and answers

Yes, when the material is clear enough to recognize the required information. Scans and photos need an OCR stage and evaluation on your samples. Illegible or cropped passages should be flagged for review rather than assigned invented values.

Multiple agreed layouts and suppliers can be supported. Samples reveal the practical limitations: a field may move and tables may span pages. New formats need to be evaluated.

No. Quality depends on the input, field types and validation rules. We evaluate errors on representative samples, check important fields separately and provide manual exception handling.

Yes. An inquiry’s text can be classified, summarized and converted into agreed fields. Routing suggestions should be distinguished from facts explicitly present in the message.

Through an available API or agreed exchange format. Before handoff, we validate fields, reference data matches and record creation rules. Failures, retries and duplicate prevention need separate handling.

Language requirements inform tool selection and sample evaluation. Document language, date formats, decimal separators and currency should be explicit rules rather than model assumptions.

Prepare a small anonymized sample set with varied quality, required fields, examples of correct output and a description of the next workflow step. This helps define a useful pilot and its dependencies.

The number of document types, table complexity, input quality, validation and integrations affect the work. Ongoing costs also depend on processing volume. We estimate after reviewing samples.

What can use the prepared information?

  • AI agents and assistants→

    Continue an approved workflow after information is reviewed.

  • AI features inside your CRM→

    Help an employee work with the record inside the system.

  • Intelligent search→

    Find information across collected materials.

START WITH REPRESENTATIVE SAMPLES

Which information does your teamstill copy by hand?

Show us the incoming material and the required result. We will identify what can be processed automatically and where review is needed.

Discuss document processing→All AI services→