DOCUMENT OCR FOR YOUR WORKFLOW
Document OCR for KYC and customer onboarding
Turn document images into fields your onboarding system can review. IdScanly provides an extraction layer for teams building their own identity and compliance workflow.
KYC & onboarding
Where manual entry slows you down
Customer journeys often need the same printed details in several systems. OCR gives your application a structured starting point, while allowing rules, human review and specialist checks to remain explicit.
A practical workflow
Capture with permission
Capture representative front and back views required by your document policy.
Extract and map fields
Normalise and map returned fields, preserving source values and confidence where available.
Review before committing
Compare against the application and run the independent identity checks required before approval.
Integrate with your existing system
Send an authorised document image from your own backend to the IdScanly REST API. Create a scan session, upload the image and retrieve structured JSON when processing finishes. Map only the fields your application needs; keep API keys on your server and handle timeouts, incomplete fields and retries explicitly.
Read the API documentationBuild a review step into the process
Document type, country, image quality and layout affect the fields returned. Use confidence information and capture feedback to request a clearer image or send uncertain records to a person. Extracting a field is different from proving it is genuine. Keep the original value separate from any correction made by an operator.
OCR supports data entry. It does not independently provide document authentication, face matching, liveness detection or a complete AML/KYC service.
Keep the data flow proportionate
Collect only what the workflow requires and explain the purpose before upload. IdScanly processes documents without building an archive; temporary processing and result retrieval can involve files and records. The marketing/admin CRM receives identity and activity metadata, never document images or OCR fields. Your own application remains responsible for its storage, retention and user permissions.
Evaluate with your own document mix
Test representative countries, document versions, front/back views and realistic capture conditions. Measure field-level accuracy and review rates against checked references before connecting the output to a live business decision. Share your expected monthly image volume and planned launch date so integration requirements can be discussed.
Questions before integration
What is the difference between OCR and identity verification?
OCR reads information from an image. Identity verification also needs evidence that the document is genuine and belongs to the person, plus any regulatory checks relevant to the use case.
Build a review step into the process
Document type, country, image quality and layout affect the fields returned. Use confidence information and capture feedback to request a clearer image or send uncertain records to a person. Extracting a field is different from proving it is genuine. Keep the original value separate from any correction made by an operator.
KYC & onboarding
Discuss this integration
Test representative countries, document versions, front/back views and realistic capture conditions. Measure field-level accuracy and review rates against checked references before connecting the output to a live business decision. Share your expected monthly image volume and planned launch date so integration requirements can be discussed.