Nanonets is an enterprise document AI platform that classifies, validates, routes, and posts documents into your ERP, billed through prepaid credits consumed per processing block. ReceiptOCR does the reading step only: upload receipts and invoices, get merchant, date, line items, tax, and total, and export Excel, CSV, JSON, or a QuickBooks file. If you need approval workflows and vendor bills written back into NetSuite, Nanonets is the better buy. If you need clean data out of documents today, upload one below and see it.
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Nanonets is aimed at organizations automating whole document processes: read the invoice, check it against a rule, look up the vendor, route the exception to Slack, post the bill to NetSuite. That is a serious product solving a serious problem. It is also a lot of machinery to stand up when what you needed was a spreadsheet by Friday.
Billing is per block run, not per document. Nanonets' own pricing page prices data extraction at $0.30 per run and notes a typical invoice workflow runs four to six blocks, so a single invoice can cost more than a dollar end to end before add-ons.
Starter begins with $50 in free credits, then $100 per month for 100 credits and up to three users. Confidence scores, analytics, and model versioning are separately metered monthly add-ons.
Growth and Enterprise are both contact-us. You cannot self-serve past the entry tier, which means a demo before you know what real volume costs.
Pre-built models exist for invoices and receipts, but reviewers on G2 and Capterra consistently describe custom document types as needing training samples and tuning. A browser upload asks for none of that.
ReceiptOCR is the extraction layer sold on its own, with no workflow engine attached. There is nothing to train, no credits to buy, and no block graph to design. Upload a batch, review the fields, take the file.
No custom model, no training samples, no schema definition. The engine reads vendors it has never seen because it was not built on templates.
A month or a year of receipts and invoices in one pass. Each document is read separately so accuracy holds across the batch.
Vendor, date, invoice number, subtotal, tax, and total, plus each line with description, quantity, and price.
Flat, by document volume. Not per block, not per run, not per user, and with no add-on meters running in the background.
Excel, CSV, JSON, and QuickBooks-ready files. Feed a ledger, a spreadsheet, or the platform you already pay for.
Every extracted field is visible and editable before export. A wrong amount is worse than a blank one, so you see the data first.
If extraction was the only part of Nanonets you actually used, this takes an afternoon.
Fifty documents that look like your real mix, including the vendors whose layouts change and the scans nobody wants to open.
Tip: Include the documents that forced you to retrain a model. Those are the test.
Compare header fields and line items against what your current pipeline returns. Extraction quality is measurable, so measure it.
Take Excel, CSV, or a QuickBooks file. If you need JSON in an application, the same engine is available over REST.
Built for US teams whose real requirement was accurate extraction and a clean file, not an agentic workflow platform with approval gates.
Many clients, uneven volume, and a spreadsheet or ledger at the end. Per-block credits are a bad match for lumpy work.
A few hundred vendor bills a month. You need them coded and posted, not routed through an agent graph.
You already have a workflow. You want reliable JSON from a document without buying somebody else's orchestration layer.
The pilot worked, the model training and block design never got finished, and the credits kept burning. Extraction alone would have shipped.
Nanonets sells what its homepage calls AI agents for enterprise data processing. The pitch is that agents read a document, validate it against your business rules, route the exceptions, and post the result into the system of record, all inside the tools you already use. Underneath the agent framing are the primitives its documentation still describes: pre-built models for invoices, receipts, purchase orders, bank statements, and passports, plus custom and instant-learning models you train on your own layouts, plus classification and routing.
It is aimed squarely at accounts payable, order management, logistics, and healthcare revenue cycle. Nanonets has native integration pages for QuickBooks and NetSuite, including two-way and three-way purchase order matching for NetSuite, and lists SAP, Xero, Sage, Salesforce, and others among its connectors. This is document processing as infrastructure, not as a utility.
Nanonets publishes per-run rates rather than a per-document price. Everything below appeared on the Nanonets pricing page and documentation in July 2026. Confirm on nanonets.com before you buy, and be aware that several third-party review sites quote figures that do not match the vendor page.
| Nanonets plan | Listed price (July 2026) | Limits |
|---|---|---|
| Starter | Start free with $50 in credits, then $100 per month for 100 credits | Up to 3 users, community support |
| Growth | Quote only, volume discounts up to roughly 40% | Up to 40 users |
| Enterprise | Custom, tailored to volume, demo required | Dedicated support and SLAs |
The credits are consumed per block run. Nanonets prices simple operations such as formatting and routing at $0.02 per run, standard AI operations such as classification and signature detection at $0.10 per run, and complex AI including data extraction at $0.30 per run. Imports run $0.04 to $0.15, exports to accounting software $0.10, and human-in-the-loop review is metered at one credit per page. Model versioning, confidence scores, and analytics are monthly add-ons at 50, 500, and 200 credits respectively.
The most useful number is the one Nanonets provides itself: a typical invoice processing workflow runs four to six blocks per document. At $0.30 for the extraction block plus imports, lookups, and exports, that lands somewhere around one to two dollars per invoice processed end to end. That is entirely reasonable if the workflow replaces a person keying the invoice and posting it. It is a strange price to pay for a CSV.
Nanonets does not lead with a single accuracy percentage anymore. Its homepage claims a first-place ranking on the IDP Leaderboard and on a benchmark it calls ComplexConstraints, states that 94% of complex document-heavy processes are automated with 6% left for human judgment, and cites a 90% reduction in processing time. A customer case study reports 93% touchless processing.
Those are process metrics, not field-level extraction accuracy, and the distinction matters. Touchless rate tells you how often no human intervened. It does not tell you how often the total was right. If you see "Nanonets is 99% accurate" quoted on a review site, note that no such figure appears on Nanonets' own current pages. Benchmark the fields you care about on your own documents.
These are not the same product, and pretending otherwise would waste your time. One automates a process. One reads a document.
| Capability | Nanonets | ReceiptOCR |
|---|---|---|
| Receipt and invoice extraction | Yes, pre-built and custom models | Yes, no training required |
| Line item extraction | Yes, with GL mapping | Yes |
| Custom model training | Yes, a core feature | No |
| Approval routing and workflows | Yes, to Slack, Teams, or email | No |
| Posting bills into an ERP | Yes, native QuickBooks and NetSuite, with PO matching | Export a QuickBooks-ready file, no write-back |
| Compliance posture | SOC 2 Type II, ISO 27001, GDPR, HIPAA BAA on enterprise plans | TLS in transit, documents deleted after processing |
| Pricing model | Prepaid credits, metered per block run | Flat, by document volume |
| Time to first result | Configuration, and training for custom types | Upload and read the fields |
Buy Nanonets when the document is the beginning of a process rather than the end of one. If an invoice has to be matched against a purchase order and a goods receipt, coded to a general ledger account, sent to a manager who approves it in Slack, and then written into NetSuite as a vendor bill, you are buying an automation platform and the credits are the cost of doing business. Its SOC 2 Type II, ISO 27001, and enterprise HIPAA BAA also clear procurement in places a lightweight tool will not.
Skip it when the honest description of your requirement is "turn these documents into rows." Paying a metered platform to produce a CSV is the most common way teams overspend in this category, and it is usually discovered nine months in, when somebody adds up the credits.
If you strip the workflow away, what remains is reading. For expense receipts that means receipt OCR software in a browser, or the receipt OCR API when the output feeds an application. For vendor bills, invoice OCR software handles the header fields and the line items, and the invoice OCR API returns the same as JSON.
Where the data lands afterward is usually a spreadsheet or a ledger. Firms handling client batches export from the bulk receipt scanner, and businesses posting their own books scan receipts into QuickBooks from the same file. If the reason you looked at Nanonets was accounts payable specifically, compare it against dedicated invoice processing software before you decide, because the AP category prices very differently. And if the API is the part you care about, the Veryfi alternative comparison covers the developer side of this market.
Buyers usually compare Nanonets against Rossum, Docsumo, Amazon Textract, Klippa, Parseur, and Docparser. The right alternative depends on what you use. If you rely on approval workflows and ERP posting, you need another platform. If you only ever used the extraction step, an extraction tool such as ReceiptOCR delivers the same fields without credits, training, or a sales call.
As of July 2026 the Nanonets pricing page lists a Starter plan beginning with $50 in free credits, then $100 per month for 100 credits and up to three users. Growth and Enterprise are quote only. Credits are spent per block run: $0.02 for simple operations, $0.10 for standard AI, and $0.30 for data extraction. Nanonets states a typical invoice workflow runs four to six blocks.
Nanonets offers $50 in free credits on the Starter plan with no credit card required, which is a trial rather than a free tier. Once those credits are consumed, Starter costs $100 per month for 100 credits. Note that several third-party review sites quote a $200 free credit figure that does not appear on the Nanonets pricing page.
Nanonets does not publish a single field-level accuracy percentage. It claims a first-place ranking on the IDP Leaderboard, states that 94% of complex document processes are automated, and reports a 90% reduction in processing time. Those are process metrics, not extraction accuracy. Any 99% accuracy figure attributed to Nanonets comes from third parties, not from its own current pages.
Not for common document types. Nanonets ships pre-built models for invoices, receipts, purchase orders, bank statements, and others. Custom or proprietary layouts use its custom model or instant learning model, which you train on your own samples. Reviewers frequently cite that training and retraining effort as the main setup cost. ReceiptOCR requires no training for any layout.
Nanonets automates a process: it reads a document, applies rules, routes exceptions for approval, and posts the result into QuickBooks or NetSuite. ReceiptOCR performs only the reading step and exports Excel, CSV, JSON, or a QuickBooks-ready file. One replaces a workflow, the other replaces data entry. Pick by which of those you are actually trying to remove.
No, and that is a real difference worth being clear about. ReceiptOCR exports a QuickBooks-ready file that you import, rather than writing vendor bills into your ledger through an API. If automatic write-back, general ledger coding, and three-way purchase order matching are requirements, a full platform earns its price. If an import file is fine, you avoid the platform entirely.
For a shoebox of receipts headed to a spreadsheet, yes. The Starter plan floor of $100 per month, per-block metering, and separately metered add-ons for analytics and confidence scores are designed for continuous, high-volume document processes. A business converting a few hundred receipts a quarter into a tax-ready file pays considerably less with a volume-priced extraction tool.
The developer API comparison, minimum commitment included.
How the AP category prices, from capture to payment.
Read vendor bills into header fields and line items.
The same extracted fields as structured JSON.
Read a large batch of receipts into one spreadsheet.
Convert receipts to a clean Excel or CSV spreadsheet.
