Product · Document AI

EveryPage

An AI platform for transforming business documents.

EveryPage uses AI to extract, summarize, classify, and analyze documents like invoices, contracts, reports, and emails. Streamline document workflows and turn unstructured data into insight.

Overview

What EveryPage is, and who it is for.

The problem

Every business sits on a pile of documents (contracts, invoices, statements, filings) that humans re-read to extract the same fields again and again. EveryPage turns that pile into a structured, queryable layer using vision-language models. You control the schema, and every extraction carries an audit trail you can defend.

Who it is for

For finance, legal, ops, and research teams that process structured-but-messy documents at volume and need extraction they can defend in audit, not just demo on a clean PDF.

Finance, legal, operations, research teams, and any business with heavy document workflows.

Capabilities

What is in the box.

  • 01

    Intelligent data extraction from structured and unstructured docs.

  • 02

    Concise automated summaries.

  • 03

    AI classification and routing.

  • 04

    Content analysis for trends, risks, and key clauses.

  • 05

    Custom reports from documents.

  • 06

    Integration with RPA and other business systems.

  • 07

    Secure handling and compliance.

In practice

How teams put EveryPage to work.

  • 01

    Process invoices and accounts payable.

  • 02

    Extract key clauses and data from contracts.

  • 03

    Analyze feedback from emails and surveys.

  • 04

    Summarize research papers and technical reports.

  • 05

    Classify and route incoming documents.

Engagement

How a EveryPage rollout runs.

  1. 01

    Document walkthrough

    60 minutes

    Bring a representative batch of your real documents. We run EveryPage live, show extraction quality on the messy edge cases, and discuss the schema you need.

  2. 02

    Schema & model configuration

    1-2 weeks

    Define the target schema per document type. Choose the VLM provider or pin to a self-hosted model, and set human-review thresholds for low-confidence fields.

  3. 03

    Pipeline deployment

    2-4 weeks

    Wire EveryPage into the upstream source (mailbox, drive, ERP, case system) and the downstream consumer (data warehouse, RPA, review queue). Run side-by-side with the human process to validate.

  4. 04

    Production cutover

    Ongoing

    Move volume onto the automated path, with the human-review queue handling the long tail. Monitor extraction drift and re-tune the schema as formats evolve.

Posture

What EveryPage commits to.

Schema-first

You own the fields

Extraction is driven by a schema you define, not a generic summarise-everything call. The output is structured data, ready for the next system.

Audit-trail

Defensible by default

Every extracted field links back to the source page and span. Reviewers and auditors can verify any value without leaving the tool.

Self-host or SaaS

Residency-flexible

Run against managed VLMs or pin to a self-hosted vision model in your VPC where regulation requires documents stay inside your perimeter.

FAQ

EveryPage: frequently asked questions

How accurate is the extraction on real, messy documents?

Accuracy depends on the document type and schema. We deliberately do not quote a single headline number. The pilot phase measures field-level precision and recall on your own corpus and sets the human-review thresholds accordingly.

Can EveryPage run entirely inside our VPC?

Yes. For regulated workloads we deploy EveryPage against a self-hosted vision-language model inside your cloud account, so document content never leaves your perimeter.

How are low-confidence extractions handled?

Every field has a confidence score and a configurable threshold. Below threshold, the field routes to a human-review queue with the source page highlighted. Above threshold, it flows downstream automatically.

What document types do you support?

Anything you can render as a page: PDFs (native and scanned), images, Office documents, and email attachments. Tables, multi-column layouts, and handwritten annotations are all in scope.

How does EveryPage stay defensible in an audit?

Each extracted value carries a citation back to the page, region, and source document. Reviewers and external auditors can verify a field without re-reading the file end-to-end.

Next step

See EveryPage against your own data.

Book a working demo, read how we evaluate the models, or follow our engineering write-ups on what we ship and why.