Faster recognition starts with a complete nurse file
Panther helps recruitment agencies in Kenya and Ghana send complete, consistent, correctly translated files for nurses seeking recognition in Germany, aiming to cut rework and place more nurses a year. AI prepares the analysis. A person decides.
Germany has almost no qualified nurses left to hire, and recognition is what holds the rest back
Nobody left to hire
Where the gap is heading
Each of Germany’s 16 states reviews foreign credentials separately. When a transcript is incomplete, mixes theory with practice, or gives credits but no hours, the file can stall after language training and matching have already been paid for.
How long recognition takes
These figures cover the whole path, including language courses and compensation measures. Panther targets the avoidable part: follow-up requests and rework caused by incomplete, inconsistent or mistranslated files.
How Panther works
A readiness report for each nurse, built from evidence and reviewed by a person.
Read
A language model reads the transcript and extracts each module or placement, its theory or clinical hours, and a German title.
Check
Plain code adds up the hours and compares them with reference requirements (2,100 theory and 2,500 practical hours). Credits-only, combined totals and “hours not recorded” are flagged as insufficient evidence, never guessed.
Review
A human advisor corrects any row. Every change is logged.
Report
Panther then generates a readiness report with an English and German summary and an action list.
Evidence first
Panther separates what a document states from what it does not.
Code does the arithmetic
The model never adds up hours, so every total can be checked and repeated.
A person decides
Panther prepares evidence. Only the authority decides who is recognised.
Who gains when files are right the first time
Recruitment agencies
Fewer follow-up requests and less rework on each file. A shorter path from first file to recognition means placements start sooner, so the same advisors can place more nurses each year.
German employers
Posts filled sooner by nurses who are recognised sooner, with less money tied up in waiting.
Nurses
A clear list of what is missing before they apply, and a quicker route to practising as a nurse. Nurses never pay.
These are our aims, not results. We will measure them in pilots, starting with the time to a complete file, where our target is to halve it.
Where we are
An early prototype. We have no real users, real files or revenue yet, and we say so plainly.
Built
- A working prototype that reads transcript text and produces a reviewed readiness report.
- Tested on one synthetic Kenyan-style transcript: 30 rows, 4 flagged as insufficient evidence.
- Tried by two nurses, on synthetic data.
- 100 recruitment agencies mapped in Kenya, Ghana and Germany.
Next
- A first pilot with agencies, on anonymised or consented files.
- An accuracy test on already-assessed files.
- OCR for scanned documents and EU hosting with consent and deletion controls.
For recruitment agencies
We are looking for a small number of agencies to test Panther on anonymised or consented files. A pilot gives you a readiness report for each file and a measured view of the time it saves.
Agencies pay, never nurses. Panther does not recruit nurses and does not promise any recognition outcome.
Or write to vizazicare@gmail.com.
Why we are building Panther
One Friday night at 10pm, my grandmother called. Her caregiver was leaving in the morning, and she had no one to take her to a doctor’s appointment. I lived 3.5 hours away. I woke up at 5am and made the drive.
Months later I moved to Germany, and the worry got sharper: what happens the next time, when I am not even in the country?
Care depends on a few trained, available people. Panther is my way of helping more of them get recognised and into the work they are qualified for.
Mercy, founder
Team
Mercy
Founder, product and operations
- MBA candidate, Darmstadt Business School
- Participant, McKinsey Forward Program
- Former business analyst, digital transformation, Boehringer Ingelheim Pharma GmbH
- Bachelor’s degree in Chemical Engineering Technology
William
Technical co-founder, chief architect
- Senior Enterprise Architect, MTN Ghana
- 15 years designing and deploying API ecosystems, enterprise architecture and cloud-native platforms
- Builds Panther’s architecture
Panther has been discussed with start-up advisors and healthcare-industry experts in Germany. The founders won a €4,000 GIZ change initiative award in 2025.