A Veryfi Alternative
Statements, Invoices & 9-Format Export

What Is Veryfi?

Veryfi vs FlowParse: different centres of gravity

It helps to frame this not as 'better or worse' but as 'built for what'. Veryfi grew up solving real-time receipt and invoice capture — point a phone at a receipt, get line items back in milliseconds — and that heritage shows in its SDKs, mobile focus and enterprise AP positioning. If your product is an expense app or a high-volume AP pipeline, that is exactly the right shape.

FlowParse grew up solving the bank-statement-to-ledger problem: take a year of messy PDF statements from any bank and produce clean, balance-validated transactions that import into QuickBooks, Xero or Excel. That heritage shows in the Smart Merge workflow, the validation engine, and native bank-feed export. Invoices and receipts are supported too, but the gravity is statements and accounting output.

So the real question is what your last mile looks like. If you just need fields in JSON to feed your own system, both work. If the deliverable is an importable accounting file or a reconciled workbook, FlowParse does that out of the box where a receipt-OCR API leaves it to you.

Validation and accuracy you can gate on

Both platforms return confidence signals, but FlowParse adds a deterministic layer on top: a 0–100 quality score with specific, explainable checks. For statements that means a balance-reconciliation test — opening balance plus the sum of transactions must equal the closing balance — which catches a dropped or misread row that a confidence number alone would miss. For invoices it means totals and tax math are verified.

That difference matters when you automate. With a hard pass/fail check you can confidently auto-accept clean documents and route only the genuinely ambiguous ones to a human, whether you're working in the app's editable preview or gating on the score returned by the validate API. It turns 'probably right' into 'provably reconciled'.

Pricing, privacy and getting started

FlowParse pricing is per page drawn from a balance, with a free monthly allowance and no signup required to try it — usage is visible per API key so cost is predictable and attributable. That contrasts with the usage- or enterprise-quote model common to receipt-OCR platforms, where evaluating the product often means talking to sales first. See the pricing page for plans.

On privacy, FlowParse processes in EU data centres, deletes the original PDF immediately after extraction, stores extracted data encrypted, and never trains models on your documents — details on the security page. Getting started is the easiest part: convert a document free in the app, then, when you want to automate, get an API key and follow the guide to parsing bank statements with an API.

Security, compliance and data residency

Financial-document tools live or die on trust, and the requirements differ by region and team. FlowParse processes documents in EU data centres, deletes the original PDF the moment extraction completes, stores only the extracted data (encrypted), lets you delete it at any time, and never uses your documents to train models — the posture is detailed on the security page. For EU-centric teams that data-residency and deletion default is often a deciding factor over a US-headquartered enterprise platform.

On access control, each API key is hashed, scoped to your account, request-counted and instantly revocable, and every call is logged with a document label and page cost for a clean audit trail. You decide retention because you control the request: store the fields you need, drop the `raw_table` if you don't, and keep PII out of your logs. That combination — strong defaults plus your own control — is designed to satisfy both a developer integrating the API and a compliance reviewer signing it off.

A real-world scenario: an accounting practice

Picture a small accounting practice onboarding a new client mid-year. The client sends a shoebox of PDFs — twelve monthly bank statements from two banks, a stack of supplier invoices, and a folder of expense receipts photographed on a phone. With a receipt-OCR-first platform, the receipts and invoices flow nicely, but the statements — the backbone of the books — need a separate converter, and turning everything into QuickBooks-ready data is still a manual assembly job.

With FlowParse, the practice runs the whole shoebox through one engine. The twelve statements are extracted and balance-validated, then Smart Merge consolidates them into a single reconciled workbook; the invoices and receipts are extracted with line items and tax; and everything exports to the formats the practice actually imports — a QBO bank feed for the statements, Excel for review. What used to be a multi-tool, multi-day onboarding becomes an afternoon.

Crucially, the validation gate means the junior who does the conversion doesn't need to eyeball every row: clean documents pass automatically and only the flagged ones — a faint receipt, a statement that didn't reconcile — get a human glance. The senior reviews exceptions, not everything. That's the difference between a tool that captures data and one that runs a workflow, and it's why practices that handle statements as well as receipts tend to consolidate onto FlowParse.

The same story scales up to a lender or a fintech: the documents differ, but the pattern — one engine, validated extraction, standard-format output, reconciliation built in — is exactly what removes humans from the routine middle of the process while keeping them in control of the exceptions. The lesson is that consolidation beats best-of-breed when the breeds don't talk to each other: two excellent point tools that each handle half your documents still leave you stitching the halves together by hand, whereas one engine that handles statements, invoices and receipts on shared rails turns that integration work into a setting.