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AI document processing dashboard

Turn invoices, contracts, and PDFs into structured data your team can trust.

An ingestion dashboard that parses messy documents into clean fields, flags exceptions, and pushes results to your finance, ops, or legal stack.

What this label means: A working demo you can try. Shows behavior we can adapt to your team's data and tools.

Problem

Documents arrive in inconsistent formats. Manual entry is slow, error-prone, and expensive. Off-the-shelf OCR misses domain-specific fields.

How it works

  1. 01

    Drop in documents

    Upload, email-in, or sync from Drive, Dropbox, S3, or a shared inbox.

  2. 02

    Extract with AI

    Vision-capable models pull line items, totals, parties, dates, and clauses on a defined schema.

  3. 03

    Review queue

    Low-confidence fields surface for one-click human review with side-by-side source.

  4. 04

    Push to your systems

    Approved records flow to your ERP, accounting, or contract management tool.

Business value

Throughput
10x
Documents per analyst, per day.
Error rate
Lower
Audit trail on every field.
Cycle time
Hours → minutes
From inbox to system of record.

FAQ

Common questions

How is this different from off-the-shelf OCR?
Generic OCR returns text. This system returns structured fields on a schema you define, with line-level confidence, exception handling, and a review queue — wired directly into your finance, ops, or contract systems.
What document types are supported?
Anything we can define a schema for: invoices, POs, contracts, statements, KYC packets, lease agreements, claims forms, vendor onboarding docs. The implementation is customized to your formats — see AI workflow automation.
What happens when the model is not confident?
Low-confidence fields drop into a review queue with the source page side-by-side. A human approves with one click. You set the confidence threshold per field.

Adapt this system to your workflow

This is a demo of an architecture we can adapt for you. Tell us your tools and workflow and we will scope what an Ideaplexa-built version looks like — timeline, integrations, and what stays a human decision.