Windows Preview available. Pro checkout is not open yet. Plans and capability details →
RowCoveAccount ↗

Plans for focused data work

Try your file.
Then choose your depth.

Preview is free. Pro unlocks the next steps: query, quality, editing, export and local MCP. Reader-specific capabilities remain visible in the app.

Preview

Get to know your data.

$0 / forever

No account. No card. Start with your own file.

Get Windows Preview
  • Supported source discovery and schema
  • Read-only first page, up to 100 records
  • Inspect nested values and field types
  • Your original file stays untouched

Pro

For large-data workflows

Go from inspection to insight.

$15 / month

Or $150 / year — save $30 annually.

  • Query, filter, sort and browse beyond Preview
  • Data quality, charts and schema comparison
  • Stage edits and save a separate copy
  • Local MCP tools for your AI workflow
  • Three active devices; manage them in Account

Renews automatically. Cancel renewal anytime. Billed upfront for the selected period. Final tax and total at checkout.

Choose the capabilities your workflow needs
CapabilityPreviewPro
Source discovery and schemaIncludedIncluded
Read-only first pageUp to 100 recordsIncluded
Full-file filters, sorting, pagination—Supported readers
Quality, chart and schema tools—Included
Reversible edits and separate-copy export—Supported readers
Authorized local MCP data tools—Included
Account requiredNoPurchase email
Active devicesNo activation neededUp to three
Know what you are buying. Monthly is billed US$15 each month. Yearly is billed US$150 upfront each year (US$12.50/month equivalent). Both renew automatically until canceled. Paddle shows the final tax and total before payment. Read the refund policy.

Billing, explained

Clear before checkout.

What is RowCove?

RowCove is a local data workspace for inspecting, querying and safely editing data files on your computer. Its native Rust data engine handles local parsing, indexing, querying and persistence for large-file workflows.

Does RowCove upload my files?

The desktop data engine processes files locally. Account services receive your email and purchase status, not your datasets. If you connect an AI client through MCP, the tool results you request are shared with that client and may reach its model provider.

What does Preview include?

Preview is free and does not need an account. Inspect supported file information, schema and up to 100 records in a read-only first page. Pro adds full-file workflows and MCP; available operations depend on the reader.

How much does Pro cost?

Pro costs US$15 per month or US$150 per year. The yearly plan is billed upfront and saves US$30 compared with twelve monthly payments. Applicable taxes and the final total are shown at checkout.

Can I cancel my subscription?

Yes. Open Account and choose Manage subscription. Cancel renewal in the Paddle portal. Access continues through your paid period; approved full refunds revoke the refunded purchase.

How does offline access work?

After activation, the app keeps a device-bound signed license. It refreshes online. Licenses last up to three days with up to one extra day of offline recovery, never beyond the paid subscription end. Reconnect periodically to keep Pro active.

Which platforms are available?

Windows is the currently validated desktop platform. macOS release acceptance is still pending. Check the release page for published builds.

Is every listed format fully editable?

No. Reader capabilities differ. CSV, JSONL, Parquet and Arrow have table workflows; database sources have explicit table selection. Some scientific and training formats currently expose metadata or archive members rather than decoded samples. See the format guide.

Who is RowCove designed for?

AI data engineers working with pretraining and post-training corpora, quantitative researchers with large market or backtest data, and people inspecting or editing GB-scale CSV, JSONL and columnar files.

Can I use RowCove for TB-scale datasets?

TB-scale datasets are a target use case for scoped access through supported shards, partitions and projected fields. A TB-scale throughput and memory benchmark has not been established. Test a representative subset and plan scan, decompression and scratch-disk costs first.

Why use a native Rust data engine?

Rust handles parsing, indexing, querying and persistence locally. Supported projection and partition pruning reduce unnecessary reads, while bounded results and virtualized views keep the desktop interface focused on the records you need.