Extract data from documents
PitCrew reads PDFs, statements, invoices, and scanned forms, identifies the fields that matter, and pulls them into structured output. Every extracted value comes with a confidence score and source reference.
Talk to an expertThe Problem
Your team is re-typing data that already exists in documents
Statements arrive as PDFs. Invoices come as scans. Forms show up as email attachments. Someone on your team opens each one and manually keys the numbers into a spreadsheet or system.
Manual data entry from documents
Account numbers, values, dates, fee amounts. Your team reads them off PDFs and types them into another system. Every keystroke is a chance for error.
Every document has a different format
Statements from one source look nothing like statements from another. Field labels change, layouts shift, and your team has to figure out where the data lives every time.
Errors compound downstream
A mistyped account number or transposed fee amount flows into reports, billing, and reconciliation. The error is only caught when something doesn't add up later.
Volume spikes at period-end
Quarter-end and year-end bring a flood of statements, tax documents, and reports. The same team that handles daily work now has to process hundreds of documents under deadline.
How It Works
From unstructured document to clean structured data in four steps
Upload documents
Drop in PDFs, Excel files, scanned images, or email attachments. PitCrew identifies the document type and selects the right extraction template.
Identify fields
The Skill scans each document and locates the relevant fields: account numbers, names, dates, values, fee amounts. Each field gets a confidence score based on extraction quality.
Extract and validate
Values are pulled into structured format. High-confidence fields pass through. Low-confidence fields are flagged for your team to verify before they enter downstream systems.
Deliver structured output
Your team gets clean, structured data with every value traced back to its source document, page, and location. Exportable as CSV, JSON, or direct system upload.
Use Cases
Where firms use Extract Data
Statement processing
Extract account numbers, values, positions, and transaction details from custodian statements, fund administrator reports, and trustee summaries.
Invoice and fee schedule capture
Pull line items, amounts, dates, and terms from invoices and fee schedules. Feed directly into billing validation or accounts payable workflows.
Onboarding form intake
Extract fields from account applications, subscription documents, enrollment forms, and KYC packages. Populate system records without manual re-entry.
Tax document processing
Pull data from K-1s, 1099s, tax returns, and annual filings. Structure the data for reporting, reconciliation, or distribution to stakeholders.
Contract data capture
Extract key terms, dates, fee structures, and obligations from agreements. Build a structured record of what was signed without reading every page.
Report digitization
Convert PDF-only reports into structured data. Performance reports, audit findings, regulatory correspondence. If the data is locked in a document, Extract Data pulls it out.
Integrations
Connects to the systems you already use
Extract Data pulls documents from your existing platforms and pushes structured output back into your systems.
40+ integrations available. If your system has an API, PitCrew can connect to it.
Frequently asked questions
Last updated:
What document formats does PitCrew support?
PDFs (native and scanned), Excel spreadsheets, Word documents, images, and email attachments. If your team can read it, PitCrew can extract from it.
How accurate is the extraction?
Every extracted field comes with a confidence score. High-confidence fields (typically 95%+) pass through automatically. Lower-confidence fields are flagged for your team to verify. You control the threshold.
Does PitCrew need templates for each document type?
PitCrew learns document layouts during setup. For common formats (custodian statements, invoices, tax forms), it recognizes field locations automatically. For custom formats, you can define extraction templates.
Can I trace extracted data back to its source?
Yes. Every extracted value is linked to its source document, page number, and location on the page. The full extraction log is available as an audit trail.
Where does the extracted data go?
Structured output can be exported as CSV, JSON, or pushed directly into your CRM, portfolio system, or accounting platform via API. You choose the destination during workflow setup.
Stop re-typing data from documents
15-minute diagnostic call. We review your document intake workflow and show you exactly where Extract Data fits.
Thanks! We'll be in touch shortly.