Tax docs, K-1s, loan applications, and insurance claims — processed in minutes, not days. AI that reads financial documents at scale, with full audit trail and compliance logging.
K-1s arrive in February. You hire seasonal staff to process them by April 15. Every year, you overpay for underskilled labor to do repetitive data extraction. AI processes the same volume with the same staff you already have.
A mortgage application requires extracting data from 20+ documents. Underwriters manually key income, employment, and asset data. The borrower waits. Your competitors who have automated this are closing faster and taking your volume.
Insurance claims require reading medical records, police reports, repair estimates, and policy documents — all in sequence. Adjusters spend 60% of their time on intake and data entry. That is not the job they were hired for.
Manual keying of capital account data, subscription documents, and investor statements introduces errors that require audit remediation. The firms that have automated document processing report 90%+ reduction in data entry errors.
Automatically identifies and routes document types — K-1, 1099, W-2, claim, policy, application — with 99%+ classification accuracy.
Trained on your specific document set. Extracts structured data from PDFs, scans, Excel, and XML with confidence scoring for each field.
Cross-references extracted data against business rules. Low-confidence or rule-failing documents route to human review with pre-filled context.
Every document processed, every field extracted, every decision made — immutably logged. Satisfies SOC 2, SOX, and regulatory examination requirements.
Extracted data flows directly to your downstream systems — Salesforce, SAP, NetSuite, core banking, or custom APIs. No copy-paste, no re-keying.
Exception review UI for your operations team. Reviewers see the document, the extracted fields, and the confidence flags side by side. Fast decisions, full accountability.
10,000 K-1s processed in 8 minutes. What your team does in 3 days, AI does before lunch.
Extract investor data, validate against fund records, and flag discrepancies — fully automated.
Automated extraction, income calculation, and underwriting data prep. Close faster with the same team.
Claims triage and routing automated. Adjusters focus on complex decisions — not data entry.
We review a sample of your document types, volumes, and current processing workflow. 1-week assessment.
Architecture document covering extraction models, validation rules, routing logic, and system integration map.
We build and test the extraction pipeline on your actual documents. Accuracy benchmarking against your ground truth.
Full pipeline in production with monitoring, alerting, and human-in-the-loop exception workflow.
Yes. Document AI is specifically designed for format variability. We train extraction models on your actual document set — not generic templates. The system handles PDFs, scanned images, Excel, structured XML, and messy legacy formats.
For structured documents (like K-1s with consistent fields), 97–99% field-level accuracy is standard. For unstructured or highly variable documents, we build human-in-the-loop workflows for low-confidence extractions rather than pretending accuracy is higher than it is.
We design the pipeline architecture with your compliance requirements built in from day one — not bolted on. That includes data residency, encryption at rest and in transit, audit logging, and access controls. We have deployed in fully air-gapped on-prem environments.
Tax forms, policy documents, and loan applications all change annually. We build adaptive extraction pipelines with version detection and exception routing. When a new form version appears, the system flags it — rather than silently extracting incorrectly.
Yes. We connect to SharePoint, OneDrive, Box, Dropbox, Google Drive, AWS S3, and most enterprise DMS platforms. Output can route to Salesforce, SAP, NetSuite, core banking, or any REST API.
From $5,000. Assessment in 1 week. Pilot pipeline in 2 weeks. Your document processing costs cut by 80%.