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 at enterprise scale.
Our proprietary framework for next-generation information extraction and resolution.
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
Generates and updates domain ontologies through natural interaction
Removes technical barriers, enabling teams to adapt structure
Integrates cleanly with existing databases and enterprise systems
Join us!
If you have world-class experience in any of the above areas or adjacent fields, please reach out. We are always hiring exception engineers!
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