Skilja
Skilja is a German company specializing in intelligent document processing and document understanding technologies that leverage advanced artificial intelligence to transform how organizations handle their document-intensive processes.
Overview
Skilja offers advanced document understanding and processing solutions designed to help organizations automate their document-based workflows and decision-making processes. Their platform combines artificial intelligence, machine learning, and deep learning technologies to extract meaning and actionable insights from documents.
Founded in 2012 and headquartered in Germany, Skilja brings over 20 years of experience in document analysis, processing, and understanding to their solutions [1]. The company focuses on developing cognitive technologies that enable machines to understand the meaning of text in documents, facilitating automated decision-making. Skilja has built a reputation for AI innovation and delivering reliable results for high-volume document processing [2].
Skilja serves organizations across various industries that need to process large volumes of documents efficiently, extract valuable information, and automate document-based decision-making. Their solutions are particularly valuable for enterprises dealing with complex, unstructured documents that require sophisticated understanding beyond basic OCR and data capture.
Key Features
- Document Understanding: AI-powered comprehension of document content and meaning
- Intelligent Classification: Automated categorization of documents by type and content
- Data Extraction: Advanced identification and capture of information from documents
- Document Separation: AI-based separation of multi-page document stacks
- Process Automation: Workflow orchestration for document-centric processes
- Machine Learning: Self-improving algorithms for continuous enhancement
- High-Volume Processing: Architecture designed for enterprise-scale document handling
- Cloud and On-Premises: Flexible deployment options for different security needs
- Integration Capabilities: APIs and services for connecting with enterprise systems
- Decision Automation: Support for automated decision-making based on document content
Products
Vinna Platform
Vinna is Skilja's fourth-generation platform for high-volume digital document processing. It features a service-oriented architecture (SOA) designed for enterprise-scale document handling. Vinna allows organizations to design custom document processing workflows in a distributed environment with options for both on-premises and cloud deployment [3].
The platform supports a hierarchical document model with batches, folders, documents, and pages, providing flexibility in data management [4]. Vinna orchestrates the various document processing components, including the LAERA suite, to deliver comprehensive document understanding capabilities.
LAERA Suite
LAERA is Skilja's suite of AI-powered document classification and extraction tools. It leverages advanced machine learning algorithms to convert unstructured document inputs into meaningful, structured information [5].
LAERA's AI-based classification and document separation are built into a sequence of algorithms that analyze and understand document content. The system automatically learns document structures from samples and applies this knowledge during runtime processing [6]. Recent updates include the integration of LaBERTa, an advanced language model for document understanding [7].
LESA OCR
LESA is Skilja's superior AI-powered OCR (Optical Character Recognition) technology. When combined with the LAERA suite, it creates an exceptionally powerful solution for converting any unstructured document input into meaningful information [5]. LESA goes beyond traditional OCR by incorporating AI capabilities that enhance text recognition accuracy and quality.
Use Cases
Intelligent Mail Processing
Organizations implement Skilja's technology to transform their mailroom operations from manual sorting to automated processing. The system receives incoming mail in various formats, including paper documents that are scanned, emails with attachments, and electronic submissions. LAERA's classification capabilities automatically categorize documents by type and department, eliminating manual sorting. Document separation features identify and split multi-page documents into logical units. Extracted information is used to route documents to appropriate workflows and update line-of-business systems. The platform maintains a complete audit trail of all document processing steps. This implementation reduces manual handling through automated document routing, accelerates processing through immediate document classification, improves accuracy through consistent extraction methodology, and enables visibility through comprehensive process monitoring.
Automated Invoice Processing
Finance departments leverage Skilja's solutions to streamline accounts payable operations. The system processes incoming invoices from multiple channels, including paper, email, and supplier portals. LAERA's advanced extraction capabilities identify and capture key invoice data including header information, line items, tax amounts, and payment terms. Machine learning algorithms continuously improve extraction accuracy through feedback loops. Extracted data is validated against business rules and ERP system information. Workflow capabilities automate approval routing based on company policies. This approach accelerates payment cycles through automated data entry, improves accuracy through consistent extraction methodology, enhances visibility through real-time processing status, and strengthens vendor relationships through timely payments and reduced errors.
Contract Analysis and Management
Legal departments implement Skilja's document understanding capabilities for comprehensive contract management. The system processes contracts in various formats and languages, extracting key clauses, obligations, rights, and deadlines. Machine learning algorithms identify contract types and critical terms that require special attention. Document comparison features highlight changes between contract versions. Automatic extraction of metadata enables systematic organization and searchability of the contract repository. Workflow capabilities support the contract lifecycle from drafting through approval, execution, and renewal. This implementation reduces risk through comprehensive clause identification, enhances compliance through systematic obligation tracking, improves efficiency through automated information extraction, and enables better decision-making through comprehensive contract intelligence.
Technical Specifications
| Feature | Specification |
|---|---|
| Deployment Options | Cloud, on-premises, hybrid |
| Architecture | Service-oriented, distributed processing |
| Document Types | Structured, semi-structured, unstructured documents |
| AI Technologies | Machine learning, deep learning, NLP |
| Processing Capacity | Enterprise-grade, high-volume capability |
| Integration Methods | RESTful APIs, web services |
| Security | Enterprise-grade security standards |
| Languages | Multi-language document support |
| Document Formats | PDF, Office documents, images, emails, and more |
| Scalability | Horizontal and vertical scaling options |
Getting Started
- Requirements Analysis: Assessment of document processing needs
- Solution Design: Configuration based on document types and workflows
- Implementation: Deployment and integration with existing systems
- Training: System training with organization-specific documents
- Optimization: Continuous improvement of processing accuracy
Resources
Contact Information
- Website: skilja.com or skilja.net
- Headquarters: Germany
- Company Size: 11-50 employees [8]
- Founded: 2012 [8]
