Send your CVs
Upload PDFs or DOCX files, forward applications to a dedicated email address, or push them through the API. Drop one CV or a whole batch — scans included.
system readyCV in, structured data outCV in.
CV in.
Clean data out.
Automatically.
Drop in any CV — PDF, DOCX, or scan — and datahone lifts the structure out: name, contact, skills, work history, and education, into clean, ATS-ready JSON. Any layout, any language, with a normalised skills taxonomy. Process one or ten thousand, delivered by webhook, the REST API, or a JSON, CSV, or XLSX download.
No card · 20 free pages / moPDF, DOCX & scansBulk, any layout, multilingual
structured candidate data
What is resume parsing?
A CV is free-form by design — every candidate lays theirs out differently — which is what makes the data inside so hard to use at scale. Resume parsing turns that document into structured, consistent fields. datahone goes past keyword scraping: it understands what each section means.
It identifies the candidate’s name and contact details, their skills, their work history, and their education — across any layout, in any language — and returns them as clean, ATS-ready JSON, with skills mapped to a normalised taxonomy. One CV or a bulk drop of thousands.
Any layoutOne model reads every CV format — columns, sidebars, infographics — with no template to set up first.
Skills taxonomyFree-text skills are mapped to a normalised taxonomy, so “JS” and “JavaScript” resolve to one searchable tag.
ATS-readyA consistent JSON shape per candidate — ready to load straight into your applicant tracking system.
simple workflow
How resume parsing works. Three steps.
Send datahone a CV, tell it where the candidate record should go once, and every CV after that runs on autopilot. You only ever touch three surfaces.
AI reads the CV
datahone handles every layout and language — pulling name, contact, skills, work history, and education, and mapping skills to a normalised taxonomy. Low-confidence fields wait for review.
nameJane Okafor
titleSenior Engineer
years_exp8
confidence0.97
Send it where it belongs
Clean, ATS-ready JSON streams to any webhook you run — in real time. Pull it from the REST API, download CSV or XLSX, or review it in the dashboard.
GETapi/v1/exports?format=csv202 queued
GETapi/v1/documents/:id/output200 ok
POST/datahone/webhook200 ok
flexible data capture
Watch it read a CV.
Point datahone at any résumé and it lifts the structure into a clean candidate record — name, contact, skills, work history, and education. Describe the fields you want, or use the ATS-ready default shape.
Jane Okafor
+44 7700 900145
Manchester, UK
Senior Software Engineer
[email protected]+44 7700 900145
Manchester, UK
Experience
Senior Engineer · Northwind · 2021–present
Engineer · Brightwell · 2018–2021
Education
BSc Computer Science · University of Leeds, 2017
Skills
TypeScriptReactNode.jsPostgreSQLAWSGraphQL
candidate.jsonextracting
{ "name": "Jane Okafor", // 0.99 "title": "Senior Software Engineer", "email": "[email protected]", "phone": "+44 7700 900145", "location": "Manchester, UK", "experience": [ { "role": "Senior Engineer", "org": "Northwind", "years": 4 }, { "role": "Engineer", "org": "Brightwell", "years": 3 } ], "education": "BSc Computer Science, Leeds (2017)", "skills": ["typescript", "react", "node", "postgresql"], "yearsExperience": 8, "status": "review_passed"}
what datahone pulls from a CV
Every field a candidate record needs.
From a one-page résumé to a six-page academic CV, datahone returns the same clean, consistent candidate record — ready to load into your ATS.
Name & contact
Full name, email, phone, location, and links — disambiguated from headers, footers, and sidebars, however the candidate laid the page out.
Work history
Each role as a structured entry — title, employer, dates, and summary — with durations computed and gaps preserved, in reverse-chronological order.
Education
Degrees, institutions, fields of study, and dates — captured as structured entries, including certifications and professional qualifications.
Skills taxonomy
Free-text skills mapped to a normalised taxonomy, so “JS”, “JavaScript”, and “ES6” resolve to one searchable tag your filters can rely on.
Multilingual
CVs in dozens of languages are parsed into the same field shape — with names, dates, and locations normalised regardless of the source language.
Bulk processing
Drop a folder of thousands. datahone parses them in parallel, flags the low-confidence ones for review, and exports clean ATS-ready records for the rest.
let AI do the boring work
Why teams run CVs through datahone.
It puts candidate data capture on autopilot, turning a folder of free-form résumés into clean, queryable records.
Seconds per CV
Stop retyping résumés into your ATS. datahone reads a full CV in seconds and returns a structured record, so a stack of applications becomes a clean dataset.
Seconds per CV, not minutes
Consistent & searchable
Every candidate comes back in the same JSON shape with skills mapped to one taxonomy — so search, filtering, and ranking actually work across your pool.
One shape per candidate
Scales to any volume
Handle a hiring spike without temp staff. You pay per page with a hard cap on every tier — overages are blocked, never billed by surprise.
Per page, hard-capped
Secure & compliant
Candidate data is encrypted in transit and at rest, scoped to your account, and never used to train shared models. EU-hosted, GDPR-aligned.
EU-hosted, encrypted
going further
Other documents datahone reads.
A CV is one document type. The same engine handles the rest of the paperwork your team retypes.
Solution
PDF parser
Pull fields, tables, and totals out of any PDF — digital, scanned, or handwritten — without a template to start.
Explore SolutionInvoice OCR
Supplier, line items, totals, VAT, dates, and PO numbers — straight from any invoice into your accounting tool.
Explore SolutionEmail parser
Turn any inbox — orders, leads, receipts, bookings — into structured data, delivered by webhook or the REST API.
Explore PlatformDocument parsing
The umbrella capability behind every solution — any document in, clean structured data out. See how datahone reads and structures your files.
Explorequestions
Resume parsing, answered.
Q · 01
PDF and DOCX CVs, plus scans and photos of printed résumés. Legacy binary .doc files are not parsed — they are declined up front with a clear unsupported-format response. Single-column, two-column, sidebar, and infographic layouts all parse into the same field shape.
Q · 02
Name, contact details, skills, work history, and education by default — with each role and qualification as a structured entry. You can add, rename, or remove fields to match your ATS schema.
Q · 03
Yes. Drop a folder of thousands and datahone parses them in parallel, returning one clean candidate record per CV. Low-confidence reads are flagged for review; the rest export straight through.
Q · 04
Free-text skills are mapped to a normalised taxonomy, so variants like “JS”, “JavaScript”, and “ES6” resolve to one canonical tag. That makes search, filtering, and matching consistent across every candidate.
Q · 05
Yes — CVs in dozens of languages parse into the same field shape, with names, dates, and locations normalised regardless of the source language.
Q · 06
To any webhook endpoint you run, pulled from the REST API, or downloaded as JSON, CSV, or XLSX, ready for the ATS or HRIS you already use. Review it in the dashboard. The JSON shape is built to map cleanly onto applicant-tracking schemas.
Q · 07
Every field comes back with a confidence score; low-confidence fields are held in a review queue for a person to confirm before the record is used. Names, dates, and locations are normalised to one consistent shape.
Q · 08
Per page, with a hard cap on every tier — a typical CV is one or two pages. When you hit your limit the next page is blocked rather than silently billed, so a bulk run can never produce a surprise bill. See pricing →
get started
Stop retyping résumés.
Drop in a CV — or a folder of thousands — and watch datahone hand each one back as a clean, ATS-ready candidate record. Free in minutes, no card required.
Any layout, multilingualSkills taxonomyATS-ready JSON