ExtractFoxExtractFox vs Nanonets
Nanonets is enterprise document AI: powerful, but expects you to upload labeled training data, train a custom model, and wait. ExtractFox uses a general multimodal model that works on the first document, no training required.
The short version
Nanonets is built for enterprises that want a custom-trained model for their exact document type. The output is high-accuracy on documents that look like the training set — but you pay for that with a lengthy onboarding (label hundreds of examples, train, iterate). ExtractFox's model is general-purpose and ships value on day one.
Side by side
| Feature | ExtractFox | Nanonets |
|---|---|---|
| Time to first extraction | 30 seconds | Days to weeks |
| Training data required | None | Hundreds of labeled docs |
| Free tier | ✓ | Limited trial |
| Self-serve onboarding | ✓ | Sales-led |
| Custom-trained models | — | ✓ |
| Multi-language | ✓ | ✓ |
| On-prem / VPC option | Enterprise plan | ✓ |
| Bulk batch processing | ✓ | ✓ |
| Pricing transparency | ✓ | Quote-based |
| Free-text custom extraction | ✓ | — |
Why teams switch from Nanonets
Nanonets onboarding is a project — gather examples, label fields, validate, retrain. ExtractFox is upload and go.
Nanonets is sales-led with quote-based pricing. ExtractFox lists tiers publicly so you can budget before talking to anyone.
When a one-off question comes in ('what's the total revenue across these annual reports'), ExtractFox lets you type the question. Nanonets needs you to add a new field to the model.
When a document layout changes, Nanonets accuracy drops until you retrain. ExtractFox's general model adapts on the fly.
Pricing
Free tier and a flat Pro subscription. Volume pricing on enterprise.
Quote-based; common deals start in the low thousands per month.
ExtractFox is dramatically cheaper for SMBs and product-led use cases. Nanonets makes sense at very high volumes with a dedicated ML team.
When Nanonets is the better pick
Pick Nanonets if you process millions of documents per month with a stable schema, have an internal ML team to manage model lifecycle, and need on-prem deployment with custom training.
Frequently asked questions
Will ExtractFox match Nanonets's accuracy on my documents?+
On standard document types — invoices, receipts, statements, IDs — yes. On highly specialized industry documents (insurance forms, claims), a custom-trained Nanonets model can edge out a general model. The trade-off is the training cost.
Can I integrate ExtractFox with my existing tools like Nanonets allows?+
ExtractFox has a REST API for paid accounts. Direct connectors and webhooks ship over time; today you can wire flows through your own backend or automation tool.
What about extracting tables with merged cells or complex layouts?+
Both tools handle these well; ExtractFox doesn't need a separate table-detection step. Try it on your worst document — if extraction is solid, that's your answer.