Our IDP solution uses advanced deep learning OCR combined with a feedback-driven learning loop. Through human validation and systematic retraining, it evolves to handle new document types and edge cases, ensuring ongoing accuracy improvements, high data integrity, and scalable cognitive automation.

Our solution combines pretrained AI models for complex documents, such as bank statements and identity documents, with flexible OCR-based extraction for other formats. Unlike static, template-driven systems, our platform is designed for adaptability; we can develop and deploy custom AI models for new document types based on client needs. This hybrid approach ensures accurate, scalable data extraction across both structured and semi-structured content, driving intelligent automation in even the most variable environments.

Accelerate your time-to-value with our pre-trained IDP solutions, including existing document models for IDs, Passports, and Bank Statements. These can be easily reconfigured to suit your specific requirements, enabling rapid deployment and streamlining your document tracking with anytime, anywhere record viewing.

Our solution offers a complete document automation pipeline; from ingestion (via web/mobile capture, drag-and-drop, bulk import, email, or API) through pre-processing, classification, extraction, and integration. To ensure high-quality data extraction, documents are automatically enhanced through exposure correction, contrast optimisation, and blur detection, with quality scoring techniques applied to assess and ensure readiness for downstream processing. This results in consistently clean, OCR-optimised inputs. Extracted data is then transformed and delivered into business systems through built-in connectors or RPA, enabling seamless Straight-Through Processing (STP) with minimal human intervention.

Our deep technical knowledge in blending the correct extraction technologies (pluggable OCR, ICR, native extraction) ensures optimal results for even the most challenging documents. We build, train, and deploy models and templates easily using intuitive configurators, whether in the cloud or on-premise.

We offer competitive and flexible pricing options tailored to your specific business needs, ensuring a cost-effective solution. Furthermore, our commitment to local support ensures you have dependable, expert assistance to guide you every step of the way.

Intelligent document processing (IDP) is a technology that automates the end-to-end journey of a document, from the moment it enters an organisation to the moment its data is usable in a business system. A typical IDP flow covers:

• Ingestion: Capturing documents via scan, web capture, mobile capture, API, single upload, or bulk upload.
• Preprocessing: Cleaning, deskewing, denoising, and preparing documents for accurate extraction.
• Classification: Identifying what type of document it is (e.g. bank statement, ID document, payslip, invoice, etc.) so the right extraction approach is applied.
• Extraction: Pulling data out using OCR, LLMs, and other AI/ML techniques
• Data manipulation: Validating, enriching, and structuring the extracted data.
• Delivery: Returning clean, usable data to downstream systems or decision engines.

Unlike basic scanning or OCR, IDP understands the document’s context and content, not just its characters.

Optical Character Recognition (OCR) is a single component. It converts an image of text into machine-readable characters. OCR doesn’t know if it just read a name, an amount, or an address.

IDP is the full pipeline that OCR sits inside of. It combines OCR with document classification, layout understanding, AI/LLM-based extraction, business rule validation, and data delivery. In short, OCR reads the text, IDP understands the document, classifies it, extracts the right fields with context, validates them, and turns them into decision-ready data.

Structured documents follow a fixed, predictable layout where fields always appear in the same place. Think application forms or ID cards with defined fields in defined positions.

Semi-structured documents have a recognisable format but with variation between issuers; bank statements, invoices, and payslips fall here, where the general layout is familiar (e.g., a “transactions” section, a “totals” line) but the exact position, headers, and formatting differ from one bank or supplier to the next.

These are the two document categories Sybrin IDP is purpose-built for, and IDP applies the right extraction technique depending on how the document is structured.

Two document types are extensively used and proven within Sybrin’s existing solutions:

• Bank and financial statements: Used within Digital Onboarding and instant loan origination use cases.
• Identity documents (national IDs, passports, driver’s licenses: Used within Digital Onboarding and Identity Verification solutions.

Beyond these, IDP can be extended to other document types such as payslips, invoices, application forms, utility bills, or contracts on a case-by-case basis, configured to the specific business use case a customer needs. Both digital-native files (PDFs, exports) and physical documents (scanned or photographed) can be processed.

Accuracy comes from combining multiple techniques rather than relying on one:

•  Preprocessing improves image quality before extraction even begins.
• Multiple extraction techniques (OCR, LLMs, and rules-based methods) are applied and cross-checked depending on the document type.
• Business rule validation catches inconsistencies (e.g., a total that doesn’t match its line items, or a date that falls outside a valid range).
• Human-in-the-loop review routes only low-confidence extractions to a person, instead of manually checking every document.
• Continuous learning improves recognition of new formats and edge cases over time.

This layered approach means accuracy isn’t dependent on any single technology getting everything right.