Texas Integrated Scope My Automation

Turn Documents Into Done

The invoice that takes twenty minutes to read, key in and file is the kind of work AI was built to erase. The problem is that "document AI" services want you to upload those invoices — your vendors, amounts and account numbers — to their cloud. We build document automation that reads and files everything inside your office instead.

Fast intake shouldn't mean uploading your books

Paper and PDFs pile up: invoices to enter, forms to route, contracts to extract terms from. Manual intake is slow and error-prone.

Cloud document-AI is fast, but it means uploading sensitive financials and client records to a third party, priced per page. We give you the speed without sending a single page out of the building.

Intake that reads

AI extracts fields from invoices, forms, receipts and contracts — typed or scanned — into structured data.

Files it where it belongs

Pushes the data into your accounting system, CRM or shared drive automatically.

Private OCR + AI on your server

The whole pipeline runs in-house; no document is uploaded to an outside service.

Exceptions, flagged

Low-confidence reads route to a person instead of silently failing — with a local audit trail.

Manual vs. cloud vs. private intake

Manual intake Cloud document AI TIS private automation
Speed Minutes per doc Fast Fast
Where docs go Filing cabinet Vendor cloud Your server
Cost Staff hours Per page One-time build + support
Sensitive data In-house Uploaded out Stays in-house
Audit trail Manual Vendor's Local, yours

Hand the filed data to an AI agent or fold it into workflow automation. Because nothing is uploaded, it's private by design.

Invoice and form intake, kept on-premise from The Woodlands to Sealy

For businesses in The Woodlands and out toward Brookshire and Sealy that can't have financials leaving the office, we stand up the OCR and AI on your own server and wire the output into the system you already use — every page stays on-premise. See our Texas service areas.

Document automation questions

What document types can it handle?+

Invoices, purchase orders, forms, receipts and contracts — typed or scanned — extracted into structured data.

Do our documents get uploaded anywhere?+

No. OCR and the AI both run on your server, so documents never leave the building.

Where does the extracted data go?+

Straight into your accounting system, CRM or shared drive — wherever you already keep it.

What about documents it can't read confidently?+

Low-confidence items are flagged to a person, with a local log, instead of being guessed.

Is there a per-page charge?+

No. It runs on hardware you own, so there's no per-page or per-document fee.

What happens when a field is low-confidence?+

It is routed to a person for review rather than guessed. The pipeline scores how confident it is on each extracted field; anything below the threshold you set is flagged in a review queue with the original document alongside it, so a human confirms or corrects it before the data is posted. Every decision is logged locally.

Can it handle our specific form?+

In most cases, yes. We tune the pipeline to the layout and the specific fields you need to pull from your forms or invoices. Clean, consistent, digital-native documents reach high field accuracy quickly; unusual layouts, messy scans, or handwriting take more tuning and lean more on human review. We test against a sample of your real documents before committing to an accuracy expectation.

Back to Business Automation · the main-site overview · the automation FAQ.

OCR / IDP options we self-host

Reading a document is the first step (OCR — optical character recognition), and understanding its structure to pull the right fields is the second (IDP — intelligent document processing). There are several mature, self-hostable engines; we choose based on your document types rather than defaulting to one. The honest caveat across all of them: digital-native PDFs hit high field accuracy, while messy scans and handwriting need review.

PaddleOCR

Layout-aware and strong on structured documents like invoices, where the position of a number on the page matters. A common first choice for invoice and form pipelines.

Tesseract

A mature, well-understood baseline OCR engine. Dependable on clean, typed text and a sensible fallback or complement when a document does not need layout awareness.

Mistral OCR

A capable self-host option for reading complex documents, useful when you want stronger extraction quality on the same on-premise principle — nothing uploaded.

DeepSeek-OCR

A multimodal option for documents that mix text with diagrams, tables and figures, where understanding the visual layout helps pull the right data.

Every one of these runs on your own server, so no document leaves the building to be read. Tool and model names move quarter to quarter — we confirm the best fit for your documents at build time.

Invoice intake pipeline, step by step

Here is what happens to an invoice once it lands — the same shape works for forms, receipts and contracts. Every stage runs on your hardware.

1. Scan

The invoice arrives — emailed, dropped in a watched folder, or scanned — and the pipeline picks it up automatically.

2. OCR

The document is read with a self-hosted OCR engine, turning the page into machine-readable text while keeping track of layout.

3. Extract fields

The AI pulls the fields you care about — vendor, invoice number, total, due date, line items — into structured data.

4. Validate

The extracted data is checked against your rules: totals add up, the vendor is known, it matches a purchase order. Low-confidence fields are flagged for review.

5. Post to accounting

Clean records post straight into your accounting system; flagged exceptions wait in a review queue for a person, with a local audit trail.

Document types & realistic accuracy expectations

Accuracy depends heavily on input quality — a clean digital PDF is a different job from a creased, photographed scan. The ranges below are directional, not guarantees; we test against a sample of your real documents before committing to a number. The point of the human-review step is that low-confidence reads never post unchecked.

Document type Realistic field accuracy Review needed
Clean digital-native PDF High — typically the strongest results Light spot-checking
Good-quality scan of a typed document Solid, a little below digital-native Low-confidence fields flagged
Messy or low-resolution scan Lower and more variable More fields routed to review
Handwritten or mixed content Most variable — depends on legibility Expect meaningful human review

Industry figures for clean digital-native documents run high, but they apply to clean inputs only — we would rather set the expectation honestly per document type than quote a blanket number.

Stop keying invoices by hand

Pick one high-volume document type and we'll automate the read-and-file on a server you own — set up on-site in the Houston area. No cloud upload.

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