Structured data out of unstructured documents
Extraction that knows
how sure it is.
Field by field.
Send a file to your pipeline by email, pull it from a connected app, or push it through the API. Lymnus parses every page — scans, photos, spreadsheets, 41 languages — returns each field with a confidence score, and routes the clean values to QuickBooks, Xero, Sheets, or back to your inbox.
No card to start
SSO & SCIM built in
1% of revenue to CO₂ removal
↳ flagged for a 10-second human check
+ 39 more
document in → clean entry out · no templates · no retyping
The data is structured the moment it's printed. Getting it into a system still means someone reads each field and types it back in by hand.
Manual entry doesn't scale
Throughput is capped by how fast a person can read a field and type it — no matter how many documents arrive.
No signal on what's wrong
A hand-keyed value looks identical whether it's right or a transposed digit. You find out downstream.
Extraction that stops at raw text
OCR to a text blob isn't structured data — you still map fields, clean them, and load them yourself.
How the pipeline runs
Configure the pipeline once. Every document after that runs the same path.
Documents enter through whatever channel fits
A dedicated email address, a connected app, a desktop upload, or a direct API call — each one lands in the same pipeline and triggers the same run.
Each field is extracted and assigned a confidence score
Scans, photos, handwriting, raw spreadsheet rows — Lymnus parses them into your fields and attaches a per-field confidence value, so you know exactly where it's certain and where it isn't.
Clean values route to the destination you set
QuickBooks, Xero, Sheets, Airtable, or an inbox — the passing records go straight through, no reformatting on your side.
Confidence-gated review
Only the fields below your threshold ever reach a human.
You set the confidence bar. Anything above it exports automatically; anything under it — a blurred total, an ambiguous date — is held as a single flagged field for a quick check. Each correction feeds back into how the pipeline reads the next one.
The metric to watch: the share of fields that clear the threshold untouched, climbing run over run.
Past the extraction step
Parsing the page is the first stage, not the whole pipeline.
Normalizes and dedupes in the same pass
Duplicate rows collapse, dates and currencies convert to one format, vendor names resolve to a single spelling — inside the pipeline, before anything exports.
41 languages into one schema
A German invoice and a Japanese receipt resolve to identical field names and types — the language of the source never changes the shape of the output.
Query your processed data in plain language
A built-in assistant runs questions across everything your pipelines have extracted — no export, no formulas, just the data you already captured.
Reports generated from the structured output
Extracted data compiles into charts, summaries, and shareable reports automatically, ready wherever your team reads them.
Multi-user by design
Share pipelines, track every edit in a visual log, roll back a change instantly, and add SSO and roles when the team grows.
The API is the same interface underneath
Post documents in, subscribe to webhooks on the way out, and script your own workflows — every pipeline action is exposed programmatically.
The output lands in your stack, not ours.
QuickBooks
Xero
Google Sheets
Excel
Airtable
Smartsheet
Google Drive
Dropbox
OneDrive
Notion
PostgreSQL
Snowflake
Zapier
Odoo
Hubspot
BigQuery
PowerBi
MySQL
Salesforce
Freshbooks
MongoDB
SharePoint
API + webhooks
Built for the teams buried in paper.
Accountable for the compute.
Parsing documents at scale draws real energy. Lymnus directs 1% of revenue to verified CO₂ removal, covering the footprint of the infrastructure your pipelines run on — at no charge to you.