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Solution: AI document processing

Your team still processes documents by hand

Documents arrive, AI identifies what each one is, extracts the fields you need and checks them against your rules. Complete, clean documents move on; the rest go to a person.

Sounds familiar?

Signs this is costing you time

Applications, onboarding packs, claims, statements, certificates, identity documents: many businesses run on documents that customers send in. Each one is opened, checked for completeness, read, typed into a system and filed. When volume rises, backlogs grow and customers wait.

The work is repetitive, but it is not trivial. Staff need to spot missing pages, wrong document types, expired dates and numbers that do not add up.

AI document processing does that first pass consistently and quickly, so staff spend their time on the documents that need judgment.

Customers notice the difference too. Instead of waiting days to learn that a page is missing, they hear within minutes exactly what to send, and their case moves forward sooner.

  • Documents arrive by email, upload, post and chat, in every format.

  • Backlogs grow whenever volume rises.

  • Incomplete submissions are discovered days later.

  • Staff retype data from documents into core systems.

  • Finding a specific document later takes too long.

Before and after

How it works today, and how it works after

Before

How it works today

  1. Documents are opened and sorted by hand.

  2. Staff check each one for completeness.

  3. Key details are typed into the system.

  4. Missing items are requested by email, days later.

  5. Files are stored in folders with inconsistent names.

After

How it works after

  1. Documents are collected automatically from every channel.

  2. AI classifies each document and extracts the required fields.

  3. Rules check completeness, dates and consistency.

  4. Customers are asked for missing items automatically.

  5. Staff review only flagged documents, in a side-by-side screen.

What we build

What we build

Multi-channel intake

Email, portal uploads, scanners and shared folders feed one pipeline.

Document classification

Each file identified as an application, ID, statement or other type.

Field extraction

OCR and a multimodal model return structured data from any layout.

Rule checks

Completeness, expiry dates, cross-document consistency and reference lookups.

Missing item requests

Automatic, specific requests to customers for what is missing.

Organized archive

Every document stored with its data and case, searchable later.

In practice

What it looks like in practice

An illustrative walk-through, not a client story.

A filing services firm asks new clients for identity documents, bank statements and previous filings. Documents arrived through email and messaging apps, and staff spent hours sorting them and chasing missing items.

Now clients upload through a portal. AI identifies each document, checks that the ID is readable and not expired, confirms the statement covers the right period and extracts key figures. If a page is missing, the client gets a specific request within minutes. Staff open a case only when everything is complete or something needs judgment. The approach reflects our filing service platform case study.

Models and tools

AI models and MCP servers that usually fit

We choose models by task, data sensitivity and cost, and test them on your real examples before we commit. These are common starting points, not a fixed recipe.

How we build it

The services behind this solution

Most solutions combine two or three of our services. These are the ones this one usually needs.

Document automation

Read invoices, forms, contracts and IDs, pull out the right fields and route them for review.

AI workflows

Step-by-step automations where AI handles the reading, sorting and drafting inside a process you control.

Customer portals

A secure place where your customers upload documents, check status, pay and message your team.

Industries where it fits best

Honest limits

Limits and human checks

Accuracy varies with document quality and type. We measure it on your own samples before launch, set confidence thresholds per field, and route anything uncertain to people. Staff always see the original document beside extracted data.

Identity and financial documents are sensitive. We use providers and regions that fit your data rules, restrict access by role, log every view and follow your retention policy. Where required, documents can be processed by models running on your own servers.

Some decisions, such as whether a document is genuine or whether an application should be accepted, should stay with trained people. The system prepares, checks and flags; it does not decide, and every decision is recorded with the name of the person who made it.

Keep exploring

FAQ

Questions about AI document processing

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