# The Enterprise Layer for Unstructured Documents

The way business users work with unstructured documents has not changed for decades.

Parsewise develops the core technology that enables **exhaustive, self-learning document processing** over long time horizons, designed for real enterprise workloads.

### >25k
### Pages per run

### >5h
### Autonomous runs

### >20k
### Requests per minute (RPM)

# Parsewise Data Engine (PDE)

PDE is built around a **structured world model**: a persistent, structured representation of everything known about the task and information available.

The result is **document intelligence that does not go off the rails** when scale or complexity increases.

Comparing approach types

**RAG-style**

| Feature                     | Parsewise         | Other Approaches   |
|-----------------------------|-------------------|---------------------|
| **Cross-Document Attention** | ✔︎ Exhaustive cross-document attention | ➖ Top-K retrieval     |
| **RL from User Interactions** | ✔︎ Feedback directly improves extractions | ➖ Prompt tuning, like/dislike  |
| **Enterprise Scalability**   | ✔︎ 100s of thousands of pages per run | ➖ ~10 files per run  |
| **KPI-Specific Models**     | ✔︎ Agents tuned to business KPIs | ➖ Model routing      |
| **Automated ontology generation** | ✔︎ Auto-generated & easy to edit  | ❌ No native, persistent ontology feature |

# Key Developments

**Cross-Document Attention**  
Modeling relationships across an entire document corpus simultaneously.

- Capture links, contradictions, and dependencies across entire corpora  
- Eliminate hallucinations by grounding outputs in all relevant sources  
- Never miss edge cases hidden outside retrieved snippets

**RL from User Interactions**   
Continuous learning system that adapts to real context.

- Trains policies directly from real user behavior, not synthetic proxies  
- Captures domain-specific preferences that static models miss  
- Continuously improves relevance, judgment, and workflow fit

**Enterprise Scalability**   
Production-grade infrastructure for very large document packages.

- Processes hundreds of thousands of pages per run with predictable SLAs  
- Elastic orchestration, queuing, and retries for spiky workloads  
- Central monitoring, audit, and versioning across projects

**KPI-Specific Models**   
Precision models tuned and validated for business KPIs.

- Built for narrow, high-value tasks using targeted fine-tuning  
- Outperform general models on structure, accuracy, and edge-case handling  
- Capture domain logic from real documents and user habits

**Automated Ontology Generation**   
Business-ready structure without engineers.

- Generates and updates domain ontologies through natural interaction  
- Removes technical barriers, enabling teams to adapt structure  
- Integrates cleanly with existing databases and enterprise systems

# [_Compare Parsewise, ChatGPT,_ _and RAG architectures_](https://arch-guide.parsewise.ai/)