Nanonets Alternative: Email Parser That Skips the Credit Math and Exports Excel, CSV, and JSON
Email-first parsing without an enterprise document platform, a credit ledger, or a training round
Nanonets is a capable AI document platform, but it is built around document workflows, priced in credits per run, and its published entry plan starts well above what most teams spend to get email into a spreadsheet. MailParse is a Nanonets alternative aimed squarely at email: name the fields you want, and it reads them from the body, from HTML tables, and from PDF, CSV, and spreadsheet attachments, then returns Excel, CSV, or JSON. Connect Gmail, Outlook, Microsoft 365, or IMAP, or POST to the REST API.
Last updated July 2026
Connect a mailbox to pull .eml/.msg in bulk, or paste a raw email to test the converter now.
Create a free account to download. No credit card required.
MailParse is a Nanonets alternative for teams whose data arrives by email rather than as a pile of scanned documents. Nanonets is an enterprise document AI platform priced in credits per workflow run, and it is genuinely strong at scanned images, classification, and ERP integration. MailParse is email-first: connect Gmail, Outlook, Microsoft 365, or IMAP, name the fields you want, and export clean Excel, CSV, or JSON. No credits to budget, no model to train first.
- No credits
- Flat plans, not per-run credit math
- No training
- Name fields, skip the sample round
- Excel / CSV / JSON
- Plus REST API and webhooks
- Free to start
- Test your real email first
Nanonets sells AI agents for enterprise data processing. Its parser is neither rule-based nor template-based: you train it on a few samples and its models then read email headers, bodies, signatures, and attachments, including scanned images. For a company processing thousands of mixed documents through an ERP, with SOC 2 or HIPAA obligations and a need for on-premise deployment, that platform earns its keep. Nobody should switch away from it for those jobs.
The friction shows up for a smaller, simpler need. Nanonets prices in credits: as of July 2026 its published Starter plan gives $50 in free credits, then runs $100 a month for 100 credits, with usage billed per run at roughly $0.02 for simple operations, $0.10 for standard AI, and $0.30 for complex AI blocks. A document that passes through several workflow blocks consumes several charges. If your actual job is turning order confirmations, invoices, or lead notifications that land in an inbox into spreadsheet rows, you end up paying for a document platform and doing credit arithmetic to forecast a bill.
MailParse does the narrower job. You connect the mailbox your email already arrives in, name the fields you care about such as order_number, invoice_total, or tracking_number, and MailParse extracts them across varied layouts, out of the body, out of HTML tables, and out of the contents of PDF, CSV, and spreadsheet attachments. You download Excel or CSV, or take JSON from the REST API and webhooks. This page compares the two honestly, including the cases where Nanonets is clearly the better buy.
Why teams choose MailParse over Nanonets for email
The differences that matter when your data arrives as email rather than as scanned documents.
Email-first, not document-first
Nanonets is designed around document workflows, with email as one ingestion route. MailParse starts at the mailbox: connect Gmail, Outlook, Microsoft 365, or IMAP and parse messages in place, so the inbox is the source of truth rather than an upload step.
Name fields instead of training a model
Nanonets asks you to train its models on sample emails before extraction is reliable. MailParse asks you to name the fields you want once, then reads them across layouts, so you are producing a usable spreadsheet in minutes rather than after a sample round.
No credit ledger to forecast
Nanonets bills credits per workflow run, at different rates for simple, standard, and complex AI blocks. A multi-block document consumes several charges, so cost forecasting means modeling your pipeline. MailParse uses straightforward plans.
Reads attachment contents
Plenty of business email keeps the real data in a PDF invoice or a CSV export. MailParse pulls fields directly out of PDF, CSV, and spreadsheet attachments in the same parse, so attachment data lands next to body data in one output file.
Clean Excel, CSV, or JSON
Get a formatted Excel workbook or CSV for review and import, or structured JSON from the REST API and webhooks for a CRM, database, or your own code. One tool covers the spreadsheet route and the automation route.
Free to start on your own email
Test MailParse on the messages you actually receive before you pay, so you judge accuracy on your formats rather than on a demo document set.
How to move an email workflow off Nanonets
Four steps to parse the same mail without credits or a training round.
Connect the mailbox or forward a sample
Link the Gmail, Outlook, Microsoft 365, or IMAP inbox the email already lands in, or forward a representative message to a dedicated MailParse address.
Name the fields you extract today
List the values your Nanonets workflow returns, such as invoice number, total, vendor, or tracking code, including anything inside PDF or spreadsheet attachments.
Check accuracy on your real email
Run a batch of your actual messages and read the columns. Because you named fields rather than trained a model, varied layouts parse without a separate sample set each.
Export or automate
Download Excel or CSV, or point the JSON output from the API and webhooks at your CRM, database, or a Zapier or Make step so the data flows without a click.
Who looks for a Nanonets alternative
Teams whose source is an inbox and whose budget does not stretch to an enterprise document platform.
Small and mid-size operations teams
Turn order, shipping, and supplier confirmations from many vendors into consistent columns, without buying a platform sized for enterprise document pipelines.
Bookkeepers & AP staff
Pull totals, dates, and invoice numbers out of invoices and receipts that arrive as PDF attachments, and hand a clean workbook to review instead of a credit invoice.
Sales & lead intake
Capture name, email, company, and message from many form and reply formats into one sheet or straight into a CRM through the API.
Developers who want a parsing endpoint
POST raw email to the REST API and get structured JSON back, without standing up an enterprise workflow builder to do it.
MailParse vs Nanonets, honestly
Scope
Nanonets is a broad document AI platform with classification, custom workflow blocks, and ERP connectors. MailParse does one job: turn email into structured fields and a clean spreadsheet or JSON payload.
Pricing model
Nanonets bills credits per workflow run, so cost depends on how many blocks each document touches. MailParse uses plain plans, which is easier to forecast for steady email volume.
Where Nanonets wins
Scanned images and OCR-heavy documents, document classification, SOC 2 and HIPAA compliance, SAML SSO, on-premise or private cloud deployment, and Salesforce, SAP, and Oracle connectors. If you need those, buy Nanonets.
Setup effort
Nanonets improves after you train it on sample documents. MailParse asks you to name the fields you want and reads them straight away, which suits smaller teams without an implementation project.
MailParse vs Nanonets, side by side
An honest feature comparison, with credit to Nanonets where it is the stronger product. Pricing changes, so verify current plans on each vendor site. To weigh the wider field, see the best email parser buyer guide and other email parser alternatives.
| What matters | MailParse | Nanonets |
|---|---|---|
| Primary focus | Email parsing to spreadsheet and JSON | Enterprise document AI and workflow automation |
| Extraction model | Name fields, reads across varied layouts | AI models trained on your sample documents |
| Pricing model | Plain plans, free to start | Credits per run, published Starter tier $100 per month for 100 credits after $50 in free credits |
| Reads attachment contents | Yes, inside PDF, CSV, and spreadsheet files | Yes, including scanned images with OCR |
| Mailbox input | Gmail, Outlook, 365, IMAP, forward, or API | Email integration into document workflows |
| Compliance & deployment | Cloud service | HIPAA, SOC 2, SAML SSO, private cloud and on-premise options |
| Best for | Teams turning inbox email into clean rows fast | Enterprises processing mixed documents through an ERP |
Nanonets capabilities and pricing come from public information on nanonets.com as of July 2026 and change over time, so confirm current details before you decide.
Frequently asked questions
What is the best Nanonets alternative?
The best Nanonets alternative depends on the source of your data. If it arrives as email and you want fields in a spreadsheet, MailParse fits because it connects your mailbox, reads named fields across layouts and attachments, and skips per-run credits. If you process scanned documents at enterprise scale with compliance and ERP requirements, Nanonets remains the stronger buy.
How much does Nanonets cost?
As of July 2026 Nanonets gives every account $50 in free credits, then publishes a Starter plan at $100 per month for 100 credits. Usage is billed per run, roughly $0.02 for simple operations, $0.10 for standard AI, and $0.30 for complex AI blocks. Growth and Enterprise tiers are quoted on request. Check nanonets.com for current figures.
Is MailParse cheaper than Nanonets?
For steady email parsing, usually yes, because MailParse charges a plain plan rather than credits consumed per workflow run. A document that passes through several Nanonets blocks incurs several charges, so cost scales with pipeline complexity. Compare your real monthly volume against both published plans rather than assuming, since vendor pricing changes.
Does Nanonets parse emails or only documents?
Nanonets parses both. It extracts data from the email header, body, signature, and attachments, and it is not rule-based or template-based, so it handles varying formats once trained on samples. The distinction is emphasis: Nanonets is built as a document processing platform, while MailParse is built around the mailbox and spreadsheet output.
Does MailParse read scanned image attachments?
MailParse reads fields out of PDF, CSV, and spreadsheet attachments alongside the email body. If your workflow depends heavily on OCR of scanned images and photographed paperwork, Nanonets is built for that and is the better fit. Choose based on whether your data arrives as digital email content or as scanned paper.
Do I have to train MailParse before it works?
No. You name the fields you want, such as invoice_total or order_number, and MailParse extracts them from the next message. There is no sample set to label and no model to train first, which is the main setup difference from Nanonets and the reason a small team can go from signup to a clean spreadsheet in one sitting.
Try the Nanonets alternative built for email
Connect a mailbox or paste an email and watch MailParse read the fields you name, from the body, the tables, and the attachments, with no credits to budget.