Implementing WorkFusion for Intelligent Process Automation IPA
WorkFusion is an Intelligent Process Automation (IPA) platform combining RPA with ML to automate cognitive tasks. Unlike pure RPA, it handles unstructured data: documents, email, images.
Where WorkFusion Outperforms RPA
Classical RPA automates deterministic processes: buttons, forms, structured data. It breaks at the slightest UI or format change. WorkFusion adds an ML layer:
- Document Intelligence: extracting data from arbitrary document formats (non-templated)
- Email understanding: classifying and extracting intent from unstructured email
- Exception handling: ML agent makes decisions on exceptions instead of passing to manual processing
- Continuous learning: model retrains on operator corrections
Typical implementation scenarios: KYC/AML document processing, invoice processing, claims handling, regulatory reporting.
Implementation Architecture
Process Assessment
Not all processes suit IPA. We evaluate:
- Volume (ROI grows with volume)
- Document and format variability
- Decision-making necessity vs. simple data copying
- Quality and audit trail requirements
Automation potential matrix: high volume + high standardization = pure RPA; high volume + low standardization = WorkFusion IPA; low volume = manual processing.
ML Models Inside WorkFusion
The platform includes pre-built models for common use cases:
- Document classification (500+ document types out-of-the-box)
- OCR + layout analysis for field extraction
- NER for data structuring
- Decision models for approval/rejection
Customization: retraining on corporate data via Active Learning workflow — ML marks uncertain cases, operators verify, model retrains.
Integration with Enterprise Systems
WorkFusion connects to: SAP, Oracle, Salesforce, ServiceNow, MS Office 365, banking core systems (via API or screen scraping). REST API + pre-built connectors for most enterprise systems.
KYC/AML Automation — Flagship Use Case
WorkFusion specializes in financial compliance. Typical KYC flow:
- Incoming document package (passport, statements, utility bills) → OCR + extraction
- Document type classification
- Field extraction (name, date of birth, address, document numbers)
- Checking against sanctions lists (OFAC, EU) via API
- Adverse media screening via NLP analysis
- Risk score calculation
- Automatic approval if low risk / handover to analyst if high risk
Before WorkFusion: 45–60 minutes per customer, manual work. After: 3–5 minutes automatically, analyst reviews only >15% cases.
Implementation Metrics
Typical WorkFusion results in banks and insurance companies:
- FTE Reduction (Full-Time Equivalent): -60–80% in automated processes
- Processing time: -70–90%
- Error rate: -85–95% (ML more consistent than operators)
- Straight-through processing (STP) rate: 75–90% transactions without human
- Payback period: 12–18 months
Implementation Timeline
| Phase | Duration |
|---|---|
| Discovery and process assessment | 3–4 weeks |
| Pilot (1–2 processes) | 6–8 weeks |
| ML training and tuning | 4–6 weeks |
| Main process rollout | 8–12 weeks |
| Hypercare and optimization | 4–6 weeks |
Total: 6–8 months to full production, with first results visible in 2–3 months.
WorkFusion licensing: subscription-based, depends on number of bots and users. For large banks — enterprise deal with custom terms.