ExtractFoxExtractFox vs Nanonets
Nanonets has moved to a self-serve, credits-based workflow builder — you chain 'blocks' (classify, extract, validate, route) and each block execution draws down credits at its own rate. ExtractFox is a single upload-and-extract step with one flat monthly quota, no workflow to assemble and no per-block pricing to track.
The short version
Nanonets used to be squarely enterprise IDP: custom-trained models, labeled data, sales-led onboarding. It's since opened up a genuinely self-serve free tier with published consumption pricing — worth knowing if you're comparing the two, since some of the old 'sales call required' framing no longer holds. What's still true is the shape of the product: Nanonets is a workflow builder where you assemble blocks and each one meters separately (simple operations, standard AI, complex AI all have different per-run rates), and its highest accuracy still comes from a model trained on your documents. ExtractFox skips the workflow-builder step entirely — one upload, one extraction, one quota.
Side by side
| Feature | ExtractFox | Nanonets |
|---|---|---|
| Time to first extraction | 30 seconds | Minutes, self-serve |
| Custom-model training available | — | ✓ |
| Free tier | 1 extraction, no signup | $200 in credits |
| Self-serve signup | ✓ | ✓ |
| Pricing model | Flat monthly quota | Per-block credit metering |
| Multi-language | ✓ | ✓ |
| On-prem / VPC option | Enterprise plan | ✓ |
| Bulk batch processing | ✓ | ✓ |
| Public pricing above the free tier | ✓ | Growth/Enterprise: quote-based |
| Free-text custom extraction | ✓ | Configure a workflow block |
Why teams switch from Nanonets
Nanonets charges per block execution — simple, standard-AI, and complex-AI runs each meter differently, so the cost of a document depends on which blocks you chained together. ExtractFox is a flat monthly extraction count regardless of document complexity.
Nanonets' model is classify → extract → validate → route, built as a chain of blocks. If you just want structured fields out of a PDF today, that's setup before your first real result. ExtractFox is upload, extract, done.
When a one-off question comes in ('what's the total revenue across these annual reports'), ExtractFox lets you type the question in the same request as the upload. In Nanonets that's a block you configure separately.
Nanonets' strongest accuracy still comes from training a model on your specific documents — useful once it's dialed in, but it drifts as your document mix changes and needs re-training to catch up. ExtractFox's general model has no training set to drift away from.
Pricing
No signup needed for the first extraction. Paid tiers run $19–$149/mo depending on volume (300–4,000 extractions/mo).
Free Starter tier ships $200 in non-expiring credits (simple runs $0.02, standard AI $0.10, complex AI $0.30 each). Growth and Enterprise tiers are quote-based with volume discounts.
Both have a real free tier now. The difference is predictability: ExtractFox's quota is a flat extraction count, while Nanonets' credit burn depends on which blocks a workflow uses, which is harder to budget against before you've built it.
When Nanonets is the better pick
Pick Nanonets if you want a model trained specifically on your document types for the highest possible accuracy, or you need a multi-step workflow (classify, extract, validate, route) rather than a single extraction step.
Frequently asked questions
Will ExtractFox match Nanonets's accuracy on my documents?+
On standard document types — invoices, receipts, statements, IDs — yes. On documents Nanonets has trained a custom model against, that trained model can edge out a general model. The trade-off is the training investment to get there.
Can I integrate ExtractFox with my existing tools like Nanonets allows?+
ExtractFox has a REST API on paid plans, currently a session-auth beta rather than a production-ready bearer-key API. Direct connectors and webhooks aren't shipped yet; today you'd wire flows through your own backend.
What about extracting tables with merged cells or complex layouts?+
Both tools handle these well. ExtractFox doesn't need a separate table-detection block — it's part of the same single extraction step.
Is there a free Nanonets alternative for low document volume?+
Both have a free tier now — ExtractFox gives one free extraction with no signup, Nanonets gives $200 in credits that you spend per block execution. For evaluating a handful of documents without building a workflow first, ExtractFox is the faster path to a result.
Do I need labeled training data to get started with ExtractFox?+
No. ExtractFox's general multimodal model extracts from the first document you upload, with no labeling or training step — that stays true whether or not you go the Nanonets custom-model route for your own use case.