Legacy systems choked on 1,000-page medical files. AI now converts handwritten notes and 1970s scans into structured data.
A life insurance technology company automates underwriting workflows that require processing massive volumes of complex documentation, from medical reports to decades-old scanned PDFs.
About 60% of underwriting cases include documentation averaging 75 pages, with some files extending to 1,000 pages of mixed text and images. A legacy...
“LlamaIndex helped us build a scalable, intelligent ingestion pipeline that understands documents, connects them to context, and keeps improving over time.”
AI-powered underwriting and medical record analysis for life insurance.
Data framework and agentic OCR platform for building LLM-powered applications.
Pathwork's Insurance document processing is part of this use case:
Related implementations across industries and use cases
Standard parsers couldn't read scientific charts. AI now extracts visuals into text, making hidden data searchable.
Paperwork-slowed brokers charged commissions for what AI now does in seconds—reading a full binder before they'd finish the cover page.
Loan officers spent hours manually scanning 500-page guidelines. Now, AI retrieves exact policies to answer clients in minutes.
Standard parsers couldn't read scientific charts. AI now extracts visuals into text, making hidden data searchable.
Hand-keying 30 fields per PDF took 10 minutes—payout errors frayed advisor trust. Document AI now handles each in under a minute.
Each incident sent engineers hunting for context from scratch, inconsistently across teams. Edwin AI now delivers it upfront.
Bond selection took days of manual review. Custom AI agents now surface risks, empowering analysts to execute trades in hours.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Legacy systems choked on 1,000-page medical files. AI now converts handwritten notes and 1970s scans into structured data.
A life insurance technology company automates underwriting workflows that require processing massive volumes of complex documentation, from medical reports to decades-old scanned PDFs.
About 60% of underwriting cases include documentation averaging 75 pages, with some files extending to 1,000 pages of mixed text and images. A legacy...
“LlamaIndex helped us build a scalable, intelligent ingestion pipeline that understands documents, connects them to context, and keeps improving over time.”
AI-powered underwriting and medical record analysis for life insurance.
Data framework and agentic OCR platform for building LLM-powered applications.
Pathwork's Insurance document processing is part of this use case:
Related implementations across industries and use cases
Standard parsers couldn't read scientific charts. AI now extracts visuals into text, making hidden data searchable.
Paperwork-slowed brokers charged commissions for what AI now does in seconds—reading a full binder before they'd finish the cover page.
Loan officers spent hours manually scanning 500-page guidelines. Now, AI retrieves exact policies to answer clients in minutes.
Standard parsers couldn't read scientific charts. AI now extracts visuals into text, making hidden data searchable.
Hand-keying 30 fields per PDF took 10 minutes—payout errors frayed advisor trust. Document AI now handles each in under a minute.
Each incident sent engineers hunting for context from scratch, inconsistently across teams. Edwin AI now delivers it upfront.
Bond selection took days of manual review. Custom AI agents now surface risks, empowering analysts to execute trades in hours.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.