🔬 Research beta · specialists · non-diagnostic

Chat guidance for OTC choices

Rule-based scoring × LLM assist. Organizes OTC options and cautions from symptoms and context. This beta lets specialists evaluate live chat behavior—not a substitute for diagnosis or prescribing.

  • Chat-first intake — describe symptoms in plain language
  • Rule-based ranking — rationale, overlap warnings, and care guidance
  • Four languages — Japanese, English, Chinese, Korean (DeepL)
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Promotional banner for the chat OTC consultation tool (beta)

01 Challenges

Three pressures on the ground

Aging populations, language barriers, and e-commerce are shifting demand—and strain—on pharmacies and shoppers alike. Gaps in counseling time can prolong uncertainty and unsafe choices.

  • Language barriers

    Visitors and residents may struggle to consult in their language and choose appropriate OTC products.

  • Staffing pressure

    Pharmacies have limited time for counseling, leaving some users uncertain.

  • Hard to choose

    Users may not know which OTC fits their symptoms and worry about safety.

02 How it works

Three steps to use

  1. Describe symptoms

    Type symptoms and context in plain language—no medical jargon required.

  2. See organized options

    Drug DB, pharmaceutical rules, and rule-based scoring are core; the LLM assists NLU and questions.

  3. Use as reference

    Review cautions and when to seek care; consult a pharmacist or clinician before buying or taking medicine.

  • Chat screen before entering symptoms (beta)
  • AI analysis progress (beta)
  • Recommended product card with match score (beta)
  • Medicine comparison response (beta)
Live Sage Terrace UI (beta): symptom input → AI analysis → recommendations and comparison.

03 Features

Four strengths

  • Safety by design

    Rule-based core; refers to in-person care when symptoms are serious.

  • Hybrid recommendation

    Rule-based scoring drives drug selection; the LLM assists NLU and questions only.

  • Four languages

    Japanese, English, Chinese, and Korean via DeepL API.

  • Accessibility

    Font sizing, text-to-speech, and collapsible sections; WCAG AA–oriented contrast.

04 Safety

Use safely

This tool does not replace medical care, diagnosis, or prescribing.

  • Seek in-person care promptly for severe or prolonged symptoms.
  • In Japan, call 119 for emergencies and use public helplines or clinics as needed.
  • If unsure about displayed information, consult a pharmacist or clinician before use.
  • Share pregnancy/breastfeeding, pediatrics, other medicines, and allergies when you can in chat.

Escalation to a pharmacist may be available depending on the deployed app version.

05 Stack

Technology stack

Beta building blocks. Rule-based logic is core for drug selection; the LLM assists.

Infrastructure (beta)

Ops & CI/CD

GitHub · GCP · Git · Linux

Frontend

HTML · CSS · JavaScript

Backend

Python · FastAPI · Docker · Gunicorn

Database

Neon · PostgreSQL

External APIs

OpenAI API · DeepL API

Multi-agent

In-house orchestration · Python · OpenAI API

More detail
  • Recommendation: proprietary rule-based scoring (symptoms, efficacy, age, interactions, etc.)
  • Multi-agent: with LLM_AGENT_ENABLED, ChatOrchestrator hands off after triage (Triage, Physical, Concierge, etc.)
  • Frontend: HTML/CSS/vanilla JS (responsive)
  • Logs: JSONL structured logs (access, performance, security)

06 Trust

Operations

Non-profit academic beta trial (per app overview documentation).

  • Source control

    GitHub versioning; CI/CD via GCP Cloud Build.

  • Production hosting

    GCP Cloud Run (asia-northeast1). Docker + Gunicorn.

  • Database

    Neon PostgreSQL (serverless) for sessions and global state.

  • Logs & monitoring

    JSONL structured logs; access, performance, and security monitoring.

Limited to healthcare, government, research, and pharmacy specialists—not a general public launch.

Try the specialist beta

Explore rule-based recommendations and LLM-assisted chat in the live UI.

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