AI Automation & OCR

Stop paying people to process documents.

Every document your team reads, enters, and files manually is time your business doesn't get back.

We automate it.

Book a Consultation See case studies

The problem

Your team shouldn't be doing this by hand.

Most operations teams process the same documents every day — invoices, shipping manifests, purchase orders, forms.

They open them. Read them. Type the data somewhere else. Someone checks it. Someone fixes it. The loop repeats.

This costs hours every week. It creates errors. It slows everything downstream — fulfilment, billing, reconciliation.

None of it needs a human.

What we build

A pipeline that reads, extracts, and routes — automatically.

Ingestion

Documents arrive via email, upload, API, or scan. The system picks them up and queues them for processing.

Extraction & validation

OCR reads the document and pulls the fields you need. Validation rules check the data before it moves.

Routing

Clean records go to the right system. Exceptions surface in a review queue. Nothing is lost or silently dropped.

Capabilities

What the system does.

Document ingestion

Accepts documents via email, upload, API, or direct scanner feed.

OCR extraction

Reads invoices, manifests, forms, and contracts — pulls out only the fields you need.

Validation rules

Checks extracted data against your business logic before it moves anywhere.

Workflow automation

Routes clean records to the right system. Flags exceptions. Triggers follow-on actions.

System integration

Connects to your ERP, TMS, accounting software, or internal database.

Audit trail

Every document processed is logged with timestamps, extracted values, and outcome.

What changes

The operational impact.

30–60 hrs

recovered per month

Teams processing 500+ documents a week typically reclaim this in manual labour alone.

97%+

extraction accuracy

For clean, consistent documents. Validation rules catch what falls below threshold.

2×

volume with same headcount

Automation absorbs growth. You scale document throughput without scaling the team.

Day 1

audit-ready

Every run is logged. Full processing record attached to every document, automatically.

Real use case

14,000 documents a month. Processed by hand.

Logistics & AI

OCR Automation Pipeline

Problem

A mid-size logistics company processed 14,000+ shipping documents monthly by hand. A team of five spent most of their day reading manifests, extracting line items, and entering them into their TMS. Errors caused shipment delays. Backlogs built up every week.

Solution

We built an OCR pipeline that ingested documents via email and portal upload. The system extracted carrier names, shipment IDs, weights, and routing codes — validated them against business rules — and pushed clean records directly into their TMS. An exceptions dashboard handled anything the system couldn't process with confidence.

Result

Manual entry eliminated for 94% of standard documents. Error-related shipment delays fell by 81%. Processing time reduced by over 60%. The team of five was reassigned to higher-value work within two months.

View all case studies

Process

From discovery to live pipeline.

Discovery

We map what you process, where documents come from, and where data needs to go.

System design

We define extraction logic, validation rules, integration points, and exception handling.

Development

We build and test against your real documents — not synthetic samples.

Integration

We connect to your systems and configure routing workflows end to end.

Deployment

Controlled rollout with team training on the exceptions dashboard.

Why Aron Tech

How we work differently.

We've built this in production

Our OCR and automation work runs in live logistics, finance, and operations environments — not demos.

Designed for your documents

Every pipeline is built around your specific document types, field structures, and validation requirements.

We don't stop at extraction

We connect the output to your real systems so data lands where it needs to go, not in a CSV to re-import.

Edge cases handled from the start

Real pipelines fail on the 3% that are blurry, rotated, or inconsistently formatted. We build for those too.

We stay involved

After launch we monitor accuracy, adjust logic as your document formats change, and extend the system when you need more.

FAQ

Common questions.

How accurate is OCR extraction?

For clean, consistent documents, extraction accuracy typically exceeds 97%. Validation rules and a human-review queue catch anything flagged as uncertain — so errors don't pass through unchecked.

Can it handle our document format?

Most likely. We train and test on your actual documents before writing extraction logic. If a format is genuinely unworkable, we'll tell you before you commit to a build.

What systems can it integrate with?

Any system with an API, database access, or file-based import. Common integrations include SAP, QuickBooks, Xero, and custom ERPs.

How long does it take to build?

A focused pipeline for a defined document type typically takes 6–10 weeks from discovery to deployment. Multi-document pipelines with more integration points take longer.

What happens when the system can't process a document?

It goes into an exceptions queue for human review. Nothing is rejected silently or pushed through with bad data.

What does it cost?