Avea builds clinical tools that give SLPs precise, real-time feedback during articulation therapy — with special focus on outcomes for patients with cleft-palate speech, post-orthognathic rehabilitation, and motor speech disorders.
Speech-language pathologists already know what good therapy looks like. They also know that delivering it consistently — across long days, mixed caseloads, and pediatric attention spans — is hard.
Avea brings machine-learning models trained on clinical phonetics data into the therapy room: not to replace the clinician's judgment, but to surface what the human ear can miss in real time.
The first product focuses on articulation analysis for patients with cleft-palate, dental-occlusion-related speech patterns, and motor speech challenges — areas where Hungarian clinical phonetics research has deep roots.
A new clinical tool earns trust by being excellent in a narrow domain before it tries to be everywhere. We are starting in three areas where machine-learning analysis can immediately help SLPs deliver better outcomes.
Real-time resonance and articulation analysis for post-surgical rehabilitation, helping SLPs and patients calibrate therapy intensity to actual measured progress.
Phoneme-accuracy scoring designed for child therapy sessions — fast feedback loops that hold attention and surface progress objectively.
Acoustic analysis for adult patients with dysarthria, apraxia, and post-stroke rehabilitation, including objective acoustic baselines and progress tracking.
Avea grew out of clinical work at the University of Szeged where the founder's interest in orofacial outcomes — particularly cleft-palate rehabilitation, where dentistry, orthodontics, and speech therapy intersect — turned into a focused engineering project. We work closely with academic clinicians at Szeged to validate every design decision against real patient outcomes.
If you are an SLP, a clinical phonetics researcher, a cleft-palate clinician, or an institutional decision-maker exploring digital tools for therapy, we would like to hear from you. Early-access members get hands-on demos and shape the first product release.
We are in a deliberate development phase with academic clinical partners. Early-access members will receive demo invitations as we open testing — currently planned for 2027. Joining the list is free and non-binding.
Avea is being designed as a clinical decision-support tool — software that helps a qualified clinician deliver therapy. It does not replace clinical judgment and is not a diagnostic device. Regulatory positioning will follow the appropriate route for the jurisdiction of sale.
GDPR-native by default. Patient audio and any clinical analysis stays on the clinic's local infrastructure unless the clinic explicitly opts in to cloud features. We are designed for the European regulatory environment first, with US HIPAA pathways planned for later.
A small Hungarian team led by Mehran Modabberi, working with academic clinicians at the University of Szeged. We are deliberately small and focused — no investors yet, no marketing budget, just clinical work and software.
We will be hiring a hardware engineer and a clinical lead in the next 12 months. If you are based in Hungary or the broader EU and want to know more, drop us a note via the early-access form and select "Other."
Clinical partnerships, research collaborations, and SLP-program pilots are how this product gets built. The fastest path is to use the early-access form and tell us a sentence about your setting. We respond to every clinical inquiry personally.