Invoices, purchase orders, receipts, contracts, forms: arriving as PDFs, scans, and email attachments, and getting retyped by hand into your accounting system. We build the layer that reads them, checks them, and files them, with a human reviewing only what genuinely needs a second look.
Live in 3–4 weeks · You own the code, the models, and the data
Trusted by teams in the US, UK, and India
Siddhraj
Unoloft
Kofeko
3nStar
Veda
Cerata
Shubham
Consultup IndiaSiddhrajUnoloftKofeko3nStarVedaCerataShubhamConsultup IndiaFive to eight minutes per invoice doesn't sound like a crisis. Four hundred invoices a month does.
But the real cost sits downstream. A transposed digit becomes a payment discrepancy that takes an hour to trace. A missed due date becomes a late fee. A PO that was never matched to its invoice becomes a supplier dispute six weeks later. Month-end takes three days longer than it should because half the ledger was entered in the last 48 hours by someone rushing.
And nobody wants to do it, so it gets deprioritised, so it gets rushed, so the error rate goes up. The manual process doesn't just cost hours, it manufactures the exceptions that cost the most hours.
Document processing pays for itself in the errors it prevents, not the keystrokes it saves.
Vendor, invoice number, dates, line items, tax, currency, and totals extracted and validated, then posted into your accounting system as a draft or a matched entry.
Three-way matching between PO, delivery note, and invoice: quantities and prices reconciled automatically, discrepancies flagged with the specific line that doesn't agree.
Photographed receipts read, categorised against your chart of accounts, checked against policy limits, and pushed into your expense tool.
Key terms pulled out: parties, dates, renewal and notice periods, payment terms, liability caps, into a searchable register, so renewals stop surprising you.
Intake forms, onboarding packs, claims, KYC documents: fields extracted, completeness checked, missing items chased automatically.
Bank statements, supplier statements, and remittance advice parsed and reconciled against your open items, with unmatched entries queued for review.
Bills of lading, packing lists, and customs paperwork read into your order or inventory system instead of a spreadsheet somebody maintains.
Faxed, photographed, skewed, and handwritten documents. Accuracy is lower and we'll tell you honestly where the line is, but a bad scan isn't automatically a no.
Not listed? Send us five real examples of the document and we'll tell you within a week whether it's a good automation candidate, before you commit to anything.
Extraction accuracy depends on the document. A clean digital PDF from a supplier who uses the same template every month is close to solved. A crumpled photographed receipt is not. Anyone quoting you a single accuracy percentage before seeing your documents is quoting you a marketing number. Here's how we handle that instead.
Posted automatically
Routed to human review, original document attached
The system doesn't just return a value, it returns how sure it is. You set the threshold. Above it, the document posts automatically. Below it, it goes to a review queue with the uncertain field highlighted and the original document beside it, so a human confirms one number in four seconds instead of typing twelve fields in six minutes.
Confidence scores only tell you whether the text was read correctly, not whether the answer makes sense. So we layer your actual rules on top: line items must sum to the subtotal, tax must be the right rate for that vendor's jurisdiction, the invoice number must not already exist, the amount must fall within the range that vendor normally bills. A perfectly-read invoice that fails a business rule still gets flagged.
Every human correction is captured. Templates for your recurring suppliers get tuned against real errors, and the exception rate drops over the first few months rather than sitting where it started. This is exactly the work the monthly plan covers: a document pipeline that nobody tunes is a pipeline whose accuracy quietly decays as your suppliers change their templates.
The goal isn't zero human involvement. It's moving humans from data entry to exception handling, and shrinking the exception pile every month.
Documents arrive however they already arrive: a monitored inbox, a shared drive or SharePoint folder, an upload form, a scanner, or an API from your supplier portal. Nobody changes how they send you things.
The system identifies what each document is: invoice, PO, receipt, contract, something unrecognised, and routes it down the right path. Unknown types go to a queue rather than being force-fit into the wrong workflow.
Fields are read, including line-item tables, using the right tool for the document rather than one model for everything. Clean digital PDFs are parsed directly. Scans and photos go through OCR first. Variable, unstructured layouts go to a document model.
Confidence thresholds and your business rules run. Duplicate checks, PO matching, tax and total arithmetic, vendor lookup against your master list, currency handling.
Clean documents post straight into QuickBooks, Xero, NetSuite, Zoho Books, Tally, Sage, or your own database. Flagged ones land in a review queue. Approvals route to the right person, with escalation when they sit too long.
Accuracy, exception rate, and throughput tracked on a dashboard you can actually see. Templates retuned as supplier formats change, alerts if the exception rate climbs. This is the monthly plan, and it's scoped in from day one.
We don't ask you to move your accounting to a new platform. The extraction layer sits in front of what you're running today.
If your system has an API, we can post into it. If it doesn't, and some older accounting software genuinely doesn't, we'll tell you before you commit, and propose a file-based import instead of pretending otherwise. We've built the accounting-sync side of this before, across QuickBooks, Xero, NetSuite, and a dozen other ledgers.
Open the email. Download the PDF. Read the figures. Type twelve fields into the accounting system. Check them. Rename and file the document.
5–8 min
Per invoice, error-prone once the pile builds up.
Read on arrival, validated against your rules, posted as a draft entry with the document attached.
Seconds
A person reviews only what was flagged.
Find the PO. Compare quantities and prices line by line. Chase the discrepancy by email. Remember to follow up.
20+ min
Whenever anything disagrees.
Matched automatically, with the specific mismatched line surfaced and the supplier query drafted.
Exceptions only
You only see the ones that actually disagree.
A backlog cleared in a rush over three days, because entry was deprioritised all month.
3 days
Errors cluster exactly where you can least afford them.
The ledger is current because entry happened on arrival, every day, without anyone scheduling it.
Day zero
Close starts from a clean position.
Every hour of data entry you remove also removes the errors that hour was going to produce. That second saving is bigger, and it never shows up on the timesheet.
Plenty of teams are well served by an off-the-shelf tool, and we'd rather say so on the call than sell you a build you didn't need.
Your documents are standard invoices, your volume is modest, your accounting system is one the tool already integrates with, and you're happy working the way the tool wants you to work. It'll be live in days and cost less upfront.
Per-document pricing has stopped making sense at your volume, your documents aren't standard invoices, your validation rules are specific to how your business actually works, you need it posting into a system nothing supports natively, or your data can't sit on someone else's platform. You also own it outright, which matters if this becomes core infrastructure.
Honest answer: we often suggest starting with an off-the-shelf tool to prove the process, and building custom once you know your real volume, your real exception rate, and exactly which rules matter. That's a much better basis for the decision than a guess made upfront.
Email and inbox automation handles mail that arrives. Workflow automation moves data between tools when the steps are known. Document processing turns unstructured files into clean, checked data. AI agents make judgement calls where the next step isn't fixed in advance. Most document-processing projects are workflow automation with an extraction layer in front, which is exactly what this page is.
The extraction model, confidence scoring, and evaluation underneath this page is its own layer, covered on Generative AI & Custom LLMs. And if the destination for that data is specifically your ERP, the connection itself is its own scope, covered on ERP systems.
Invoices and contracts are among the most sensitive things a business handles. Three questions we get asked every time, answered plainly.
Hosting is scoped to your project, with regional hosting available where data residency (for example EU or UK) is a requirement. We'll confirm the exact setup before any documents move.
No. We use commercial API tiers with training disabled, or self-hosted models where you need the data to never leave your environment. We'll show you exactly which providers are in the pipeline before you sign anything.
Access is limited to the engineers on your project, under NDA, with access logged. We sign NDAs before discovery and work under a standard MSA and SOW with clear IP transfer terms.
Retention is configurable per project rather than fixed, so processed documents and extracted data are kept only as long as you need them.
See what the monthly plan actually covers, the tuning work that keeps accuracy from decaying as supplier formats change.
Book a 30-minute call. We'll look at your actual documents, tell you honestly what accuracy to expect and where the exceptions will be, and give you a fixed price if it's worth building.
