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AI and Automation

PDF Data Extraction

Reliable structured data from any PDF format.

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Overview

What we deliver

We build PDF data extraction pipelines that turn unstructured and semi-structured documents into clean structured data ready for analytics and downstream systems.

We build PDF data extraction pipelines for businesses that need reliable structured output from documents that vary in layout, quality, and format. Our pipelines handle native PDFs, scanned PDFs, mixed-page bundles, and complex layouts with tables, footnotes, and multi-column text. We combine OCR, layout-aware parsing, and large language models to extract fields and tables accurately, and we build validation rules to catch errors before data lands in your systems. Output flows to databases, data warehouses, spreadsheets, or APIs in the schema you need. We also build review queues for low-confidence results so your team only touches the documents that need attention. Whether you are extracting financial statements, lab reports, shipping manifests, or research data, we tune the pipeline to your document types and accuracy targets. The result is reliable structured data ready for analytics, reporting, and operational workflows.

Fit Check

Built for teams like yours

Who it's for

  • Operations teams
  • Data analytics teams
  • Research organizations
  • Financial services firms
  • Healthcare administrators

Pain points we solve

  • Locked data in PDF formats
  • Inconsistent table extraction
  • Manual rekeying of reports
  • Slow data availability
  • Errors from copy-paste workflows
What's included

Capabilities

Everything we cover in this engagement.

  • Layout-aware parsing
  • Table extraction
  • Field-level validation
  • Multi-page handling
  • Schema-driven output
  • Confidence scoring
  • Review queue tooling
  • System integration
How we work

Our process

A clear, predictable path from kickoff to outcomes.

01

Document review

We sample your PDFs and document layout variations.

02

Schema design

We agree on output fields, tables, and validation rules.

03

Pipeline build

We construct extraction stages and integrate destinations.

04

Validation

We measure accuracy against ground truth samples.

05

Go-live

We deploy with monitoring, alerts, and review workflows.

What you get

Deliverables & outcomes

What you get

  • Extraction pipeline
  • Output schema documentation
  • Review queue interface
  • Destination integration
  • Accuracy report
  • Maintenance runbook

Outcomes you can expect

  • Faster data availability
  • Higher extraction accuracy
  • Lower manual workload
  • Better downstream analytics
  • Reduced rekeying errors
Timeline

4 to 8 weeks

Engagement

Monthly retainer, Project, Sprint

Tools we use

Azure Document Intelligence, AWS Textract, Google Document AI, OpenAI, Python

KPIs we track

Field accuracy, Table accuracy, Documents per hour, Manual review rate, Time to data

Client stories

What clients say

"

Our LCP was 4.8 seconds and Google was punishing us for it. They audited the build, dumped two plugins we did not need, moved hero images to a real CDN, and rewrote the critical CSS. LCP came down to 1.6 seconds within three weeks. Bounce rate on the pricing page dropped by a quarter without us touching the copy.

Sarah K.
"

Two weeks before our seed round we still did not have a defensible model. Their fractional CFO rebuilt our three-statement forecast, pressure-tested the assumptions, and walked me through every line before the partner meeting. We closed 1.4M on the terms we wanted. The investor specifically called out how clean the financials looked compared to the last five decks she had seen.

Hannah B.
Proof

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FAQ

Frequently asked questions

Quick answers to the questions we hear most.

Can you extract tables from PDFs?
Yes, we handle simple and complex tables including merged cells, multi-page tables, and tables without visible borders.
What about scanned PDFs?
We apply OCR for scanned content and combine it with layout parsing for native PDFs, often within the same document.
How do you measure accuracy?
We benchmark against ground truth samples you provide and report field-level and document-level accuracy in the pilot.
Where does the data go?
We send output to databases, data warehouses, spreadsheets, APIs, or any destination you specify in the agreed schema.
What if the layout changes?
We build pipelines to handle layout variation and we monitor for drift, with retuning included in retainers.

Need clean data from your PDFs?

We will run a pilot extraction against your real documents and report accuracy by field.

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