Before outbreaks become official data, they become human symptoms.
SymptomSignal helps people report symptoms in any language by voice or text — and turns those reports into privacy-preserving early signals public-health teams can review.
Not for emergencies. If symptoms are severe or urgent, contact local emergency services.
- Private by design
- All-language intake — validated language packs over time
- Built for public health
- Not a diagnostic tool
- Human-reviewed alerts
Tell us in your own words. Any language is okay.
Not another symptom checker.
SymptomSignal is not built to diagnose individuals. It is built to help people track symptoms safely and help public-health teams see privacy-preserving community patterns earlier.
Symptom journal for people
A calm, multilingual way to track how you feel over time.
Signal intelligence for public health
Aggregated, privacy-preserving patterns — never individual records.
Human review before action
Trained reviewers and epidemiologists decide what matters.
Two urgent needs.
Explain what you feel, in your own language.
Speak or type symptoms naturally. SymptomSignal asks a few clarifying questions, checks for warning signs, helps you track changes, and creates a doctor-ready summary when needed.
- Voice or text symptom reporting
- Daily symptom journal
- Red-flag safety guidance
- Doctor-ready summary export
- Private by default
See the signal before the surge.
Aggregated symptom reports become privacy-preserving community signals, helping public-health professionals identify unusual patterns, monitor clusters, and decide what deserves review or investigation.
- Privacy-safe heat maps
- Composite signal scoring
- Epidemiologist Workbench
- Data quality labels
- Lead-time and false-alarm tracking
From one symptom story to an early public-health signal.
Specialized check-in surfaces
Conferences, schools, camps, sports tournaments, religious gatherings, shelters, senior living, cruises. Organizers see only privacy-safe aggregate signals — never who reported.
Open Event WatchPrivacy-first travel symptom intelligence. No exact seat, no passenger name, no ticket number. Aggregate signals only, with strict privacy thresholds.
Open Travel WatchDesigned for a sick person, not a spreadsheet.
When someone feels unwell, the experience must be simple, calm, and useful in under 90 seconds.
Speak or type. Any language.
Green / Yellow / Red.
Plain-language guidance.
30-second check-ins.
Export when ready.
Built for the questions public-health teams actually ask.
Is something unusual happening? Where? Since when? Compared to what baseline? How confident are we? What should we do next?
Based on report volume, onset clustering, severity, geography, and data quality.
- Data Quality: Moderate
- Language confidence: High
- Duplicate risk: Low
- Location precision: Region-level
- External corroboration: Pending
User-reported fever, cough, fatigue, and sore throat increased above baseline. Onset dates cluster within 72 hours.
Recommended next step: compare with ED, wastewater, lab, and school absenteeism data.
The missing layer in public-health surveillance.
“SymptomSignal does not replace surveillance systems. It gives them an earlier human signal.”
Privacy is not a feature. It is the foundation.
Users can keep symptom journals private and choose whether to contribute anonymously.
Public maps show only aggregated, privacy-safe regions. Individual reports are never displayed.
SymptomSignal identifies symptom patterns and warning signs. It does not diagnose or replace clinicians.
AI can detect and summarize signals, but high-impact public-health actions require authorized human review.
Illness does not speak one language. Neither should public health.
SymptomSignal supports all-language intake from day one, with validated language quality expanding over time.
The platform accepts symptom reports in any Unicode language, detects language automatically, supports right-to-left layouts, and translates reports into structured symptom concepts. High-volume languages can be validated with reviewed symptom vocabulary, safety phrasing, and public-health messaging.
- EnglishI've had a fever for two days.
- EspañolLlevo dos días con fiebre.
- РусскийУ меня уже два дня температура.
- العربيةعندي حمى منذ يومين.
- 日本語二日間熱が続いています。
- हिन्दीमुझे दो दिन से बुखार है।
Where early signals matter.
Track privacy-safe respiratory, fever+rash, and GI symptom patterns across classrooms or cohorts.
Add community-reported symptom intelligence to public-health monitoring workflows.
Detect symptom clusters across campus before clinics and labs show a surge.
Monitor post-event illness signals using anonymous QR-code reporting.
Support early awareness of respiratory and GI illness patterns in high-risk settings.
Enable multilingual symptom reporting in communities with limited formal healthcare access.
Stronger signals come from multiple layers.
Start with a focused pilot. Prove the signal.
Monitor fever, cough, sore throat, fatigue, and test results across a defined community.
Track vomiting and diarrhea signals with privacy thresholds and school nurse review.
Use QR-code reporting before and after large gatherings to detect emerging symptom patterns.
Real operational entry points
Not just "public health." Each pilot type has a defined operator, a defined population, and a defined signal.
Nurses see daily symptom check-ins from students (with parent consent), flag GI or fever clusters early, and coordinate with district health staff — no names exposed in signals.
Voluntary reporting via QR codes in dorms, dining halls, and clinics. Student health services get pre-clinical signals by building or campus zone.
QR codes at entry, on badges, and post-event emails capture symptom reports across the event window. Organizers and local public health get a shared signal view.
Voice and text reporting in the languages people actually speak at home. Community health workers and trusted messengers route signals to local health authorities.
Staff-assisted check-ins flag respiratory and GI changes across a facility before formal case counts — supporting infection prevention teams with earlier visibility.
Clear boundaries. Safer deployment.
- Help people describe and track symptoms
- Screen for urgent warning signs
- Identify possible symptom patterns
- Generate privacy-preserving community signals
- Support public-health review workflows
- Diagnose disease
- Replace a clinician
- Declare official outbreaks
- Provide definitive disease probabilities
- Sell symptom data
- Display exact personal location publicly
Built by a healthcare technology entrepreneur.
Founded by Tatyana Kanzaveli, a healthcare technology entrepreneur and AI builder with years of experience developing digital health platforms, patient-facing applications, and data-driven care systems.
SymptomSignal is being developed with a safety-first, privacy-first approach and is actively seeking scientific advisors, public-health collaborators, and pilot partners.