RaccoonDoc
RaccoonDoc is a cloud-native IDPaaS platform from Kyiv, Ukraine achieving up to 98% data extraction accuracy with 25x faster processing than manual methods.
Overview
RaccoonDoc emerged from Innora, a Kyiv-based UiPath Gold Partner and RPA system integrator, launching in 2021 as war broke out in Ukraine. The platform provides IDP as a Service (IDPaaS) using machine learning, computer vision, and neural networks for structured and unstructured data extraction from complex documents.
In January 2026, RaccoonDoc expanded beyond Innora's direct partnerships by launching the RaccoonDoc Activities connector on UiPath's marketplace, positioning itself as a zero-setup IDP solution requiring no templates or training. The 100% cloud-native solution combines automated ML-based extraction with in-house human-in-the-loop (HITL) review teams, now claiming up to 100% accuracy on returned data through hybrid rules-based processing, ML models, and continuous neural network retraining.
Key Features
- IDPaaS (IDP as a Service): Fully cloud-native platform without on-premise infrastructure requirements
- Zero-Setup Processing: No templates or training required for document processing
- UiPath Integration: REST API connector compatible with UiPath Studio 21.10-22.10+ requiring Windows runtime with .Net 5.0+
- Hybrid Architecture: Combines rules-based processing, ML models, and human validation with self-learning neural networks
- Multi-Format Support: Processes images, photos, PDFs, emails with multi-page and multi-type document handling
- Human-in-the-Loop Validation: In-house HITL team reviews extractions with 100% accuracy guarantee
- Continuous Learning: Self-retraining neural networks without manual intervention
Use Cases
Enterprise RPA Integration
Organizations deploy RaccoonDoc through the UiPath marketplace connector for plug-and-play IDP capabilities within existing RPA workflows. The zero-configuration approach eliminates setup overhead while processing unlimited document volumes through hybrid rules, ML models, and human validation.
Complex Document Analysis
Companies with unstructured or variable-format documents implement RaccoonDoc for extraction tasks beyond standard templates. The platform's self-learning neural networks adapt to customer document types without manual training, applying computer vision to extract data from layouts that challenge traditional OCR systems.
Accuracy-Critical Processing
Enterprises in sectors with fiduciary responsibilities use RaccoonDoc for high-stakes document processing where the 100% accuracy guarantee through HITL validation is essential. The hybrid architecture ensures continuous improvement while maintaining reliability for downstream systems.
Technical Specifications
| Feature | Specification |
|---|---|
| Platform Type | Cloud-native IDPaaS |
| Deployment | 100% cloud |
| Core Technologies | Hybrid rules, ML models, computer vision, neural networks |
| UiPath Compatibility | Studio 21.10-22.10+, Windows runtime, .Net 5.0+ |
| Document Processing | Images, photos, PDFs, emails (multi-page, multi-type) |
| Claimed Accuracy | Up to 100% (with HITL guarantee) |
| Setup Requirements | Zero templates or training required |
| Learning Capability | Self-retraining neural networks |
| Parent Company | Innora (UiPath Gold Partner) |
Resources
Company Information
Headquarters: Kyiv, Ukraine
Parent Company: Innora (UiPath Gold Partner, RPA system integrator)
Founded: 2021
Context: Launched during wartime, continuing operations