AI-powered neuro-language assessment

Objective language recovery analysis.

Neurolexi develops clinically grounded neurotechnology for the analysis of language recovery and speech processing in aphasia — measuring speech onset, pronunciation accuracy and naming latency with precision.

Swiss-based & encrypted Evidence-based aNL detection
Developed with n|w FHNW · Swiss made · Clinically grounded · Privacy first
Brain and speech-waveform motif representing Neurolexi neuro-language analysis
2.45s avg. naming latency
Why Neurolexi

Clinical insight, built on neuro-language intelligence

Four principles shape every measurement Neurolexi produces — from the patient app to the therapist dashboard.

Secure & private

Swiss-based hosting and end-to-end data encryption keep patient data protected.

AI-powered

State-of-the-art models for speech recognition and automatic naming-latency analysis.

Neuro-language intelligence

Advanced aNL detection surfaces deeper clinical insight than manual scoring.

Evidence-based

Built on peer-reviewed research and clinical best practice with Swiss institutions.

How it works

From a spoken word to an objective result

A picture-naming task on the patient app becomes a clinically meaningful measurement in seconds — recorded, analysed and stored, ready for the therapist.

1

Patient app

A visual stimulus is shown to the patient on a tablet.

2

Patient response

The patient speaks the name of the identified object.

3

Audio upload

The audio waveform and data packet are securely transmitted.

4

ASR & aNL analysis

Whisper validates the spoken word; the FHNW algorithm detects naming latency.

5

Result

The validated result is sent back to the patient app.

6

Secure storage

Results are stored safely in an encrypted PostgreSQL database.

7

Therapist dashboard

Data becomes available for evaluation, analytics and reporting.

Neurolexi technical flow: patient app, ASR and aNL analysis, secure database and therapist dashboard

ASR & aNL analysis runs at api.neurolexi.ch using Whisper validation and the FHNW automatic naming-latency algorithm.

Therapist dashboard

Every session, measured and visualised

Naming latency, pronunciation accuracy and overall progress are tracked over time — turning subjective observation into objective, comparable data.

  • Naming latency over time — average response time tracked across sessions.
  • Pronunciation accuracy — correctness scored automatically per item.
  • Session analytics — items practiced, self-corrections and latency improvement.
2.45 sAvg. naming latency▼ 0.58 s vs. last 4 weeks
78 %Pronunciation accuracy▲ 9 % vs. last 4 weeks
Neurolexi therapist dashboard on a tablet showing naming latency and pronunciation accuracy
Building Neurolexi

From research project to certified medical product

The areas below shape how we grow Neurolexi responsibly — combining scientific rigour with the discipline of building a regulated health technology company.

Business organisation

Operations

Lean structures, clear roles and quality-managed processes that scale from spin-off to operating company.

Research & development

R & D

Continued algorithm research with the FHNW, advancing automatic naming-latency detection and speech analysis.

Sales & marketing

Go-to-market

Reaching clinics, speech-language therapists and research partners across Switzerland and beyond.

Funding & finance

Finance

Sustainable financing, grant strategy and transparent governance to fund long-term clinical impact.

Regulatory & quality

Certification

A clear path toward medical-device conformity (ISO 13485 / MDR) and clinical validation.

Digital neurorehabilitation

Vision

Contributing to the future of digital neurorehabilitation through research-driven neurotechnology.

Clinical research

Grounded in peer-reviewed science

The Neurolexi method is based on clinically tested naming-latency analysis and speech-processing research conducted with Swiss research institutions.

2026Article

Can an initial phoneme-based algorithm improve automatic naming latency detection during picture naming tasks? A feasibility study

Rickert E., Altermatt S. et al. — Biomedical Signal Processing and Control, Vol. 113, Part B, 2026, 108851.
View publication
2021EMBC

Evaluation of the potential of automatic naming latency detection for different initial phonemes during picture naming task

Park S., Altermatt S. et al. — 43rd Annual International Conference of the IEEE EMBS (EMBC), 2021, pp. 945–950.
View publication
Get in touch

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