We help companies reduce manual retyping, checking and forwarding of data from documents, invoices, PDF files, forms, emails, attachments, scans and photos.
We do not start with OCR alone. First we check which documents reach the company, which data is needed from them, where exceptions appear and what should happen after extraction.
Who is document automation for?
This service is for companies where documents, attachments or PDF files trigger further work: invoicing, approval, ticket handling, reporting, system updates or customer contact.
- employees manually retype data from documents,
- invoices, forms or PDF files arrive by email and need handling,
- document data must be entered into Excel, CRM, ERP or an accounting system,
- documents must be classified by case type,
- attachments require checking, approval or forwarding,
- scans and photos contain data needed in the process,
- the team loses time checking document completeness,
- reports are created only after data is manually collected from files.
Typical document problems
Manual data retyping
Data from invoices, PDF files, forms or photos is manually moved into Excel, CRM, ERP or a report.
Documents arrive through different channels
Files arrive by email, form, as a scan, photo, PDF or customer attachment.
Missing classification
The team must manually recognize whether a document is an invoice, order, protocol, complaint, ticket or another case type.
Hard to check completeness
It is not immediately clear whether the document contains all required data, attachments or signatures.
Data does not move forward automatically
After extraction, someone still manually passes the data to a system, report, email or approval step.
Exceptions stop the process
An unusual format, missing fields, poor scan quality or unclear content require a human decision.
What can be automated in document handling?
- data extraction from invoices, PDF files, forms, scans and photos,
- document and attachment classification,
- missing information detection,
- preparing data for Excel, CRM, ERP or an accounting system,
- exception handling and handoff to a human,
- generating document summaries,
- automatic status assignment,
- creating reports based on documents,
- integrating documents into the downstream workflow,
- archiving and maintaining document history.
OCR is only one part of the process. The biggest value appears when the extracted data reaches the right place: approval, report, system, export or further handling.
Which documents can be analyzed?
- invoices,
- orders,
- forms,
- protocols,
- service tickets,
- work sheets,
- warranty documents,
- transport documents,
- PDF files from customers,
- scans,
- photos,
- email attachments,
- summaries and reports,
- documents requiring approval.
Not every document should be fully automated right away. Sometimes the best first step is extracting a few key fields, classifying the document type or preparing the data for manual approval.
Where is the best place to start?
The best first scope is one document type and one specific process. That makes it possible to quickly check extraction quality, typical exceptions and real time savings.
- one document type, for example invoices or forms,
- a few key fields to extract,
- document classification by type,
- data completeness checks,
- export to Excel or CSV,
- handing data over to a system,
- a simple approval panel,
- a report with results and exceptions.
You do not need to start with full automation of the entire document workflow. Often one document type, one team and one clear success criterion is enough.
How we work on document automation
- 1. You describe the documents and process — We check which documents reach the company, where they come from, who handles them and what happens to the data after extraction.
- 2. We choose the first document type — We do not automate everything at once. We choose the document that is repetitive and gives real value after automation.
- 3. We check data and exceptions — We analyze file quality, document layout, missing fields, unusual cases and risks of incorrect extraction.
- 4. We choose the solution — It can be OCR, AI, validation rules, integration, export, a dashboard or a simple approval panel.
- 5. We test a pilot — We test the solution on a limited document set and decide whether it is worth expanding.
- 6. We decide what comes next — After the pilot we can extend the scope, add integrations, more document types or automatic reporting.
What we do not promise with OCR and AI
- We do not promise 100 percent extraction accuracy for every document.
- We do not assume every document can be automated immediately.
- We do not remove people from the process where review or decisions are needed.
- We do not deploy OCR without checking what should happen to the data after extraction.
- We do not recommend a large system if a small pilot, export or approval panel is enough.
In practice, the best document implementations combine automation with human control. The system should read, organize and suggest, but exceptions must go to the responsible person.
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- How we work
Do you have documents that someone still handles manually?
Describe which documents reach the company, which data needs to be extracted and what happens next. We will check whether it makes sense to start with OCR, AI, automation, integration, data export or a simple approval panel.
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