Mahad ecosystem case study
Mahad Resume
CV import and structured candidate profiles
The problem
Mahad Resume receives CVs in many layouts. Reading each one by hand to build a candidate profile is slow and inconsistent, and typing errors travel into every downstream record.
Document workflow
- 1A CV arrives as PDF or image
- 2The file is sent to the Mahad OCR API with the tenant’s own API key
- 3Mahad OCR extracts contact details, skills and experience
- 4The structured profile is reviewed before it is saved
How Mahad OCR is used
Mahad Resume holds a real Mahad OCR tenant with its own API key, created through normal self-service signup — not a backdoor. Documents processed to date are real CVs and identity documents.
Data extracted
- name, email, phone
- skills
- work experience entries
- identity document fields where supplied
Verified status
Verified in production: a Mahad Resume tenant exists with processed documents and metered usage. Volume is still small — this is a pilot, not a fully rolled-out integration.
Review and correction
Disputed, unreadable or missing fields are routed to the review queue and corrected by a person before the profile is used.
API connection
Standard REST API with a tenant API key — the same integration path any external customer uses.
Operational benefit
Profiles are built from extracted data instead of manual retyping, and every document keeps an audit trail.
Try it on your own document
Run the live demo, or create an account and get an API key.