评委您好 — 如果您想先用中文快速了解产品逻辑与测试路径,请直接阅读 评委导览(中文)。
The loop
missed terms
Teacher
a source, or a meeting topic
Producer agent
aligns & curates courses
Briefing agent
researches & writes briefings
Courses & Briefings
parallel-reading + pre-meeting
Students practice
sight interpretation, aloud
AI scoring
accuracy · terms · fluency
Flashcards
spaced repetition (FSRS)
Dashboards
progress & class-wide trends
Terminology base
shared across every course
Producer — course production
The teacher points at a bilingual source (or picks from daily auto-discovered candidates). The Producer agent aligns it paragraph by paragraph, curates terminology across the whole document, and publishes a parallel-reading course — typically in minutes.
Briefing — pre-meeting preparation
Given a meeting topic, the Briefing agent researches the web, cross-checks sources, and delivers a 9,000-character pre-meeting knowledge briefing: domain crash course, speaker and institution profiles, contested issues, and a graded bilingual term table.
Practice — sight interpretation
Students interpret real sentences from real courses, out loud. A multimodal model listens to the audio directly and scores accuracy, terminology, and fluency — then routes every missed term into that student’s flashcard queue.
Classroom — management & analytics
Teachers create classes with invite codes, watch per-student averages, and see the terms the whole class keeps missing — data deciding what next week’s lesson should be.
Why agents, not a chatbot
A chatbot answers questions; a classroom needs artifacts: a finished course, a finished briefing, a finished score. InterpScout’s agents run as durable, long-lived sessions that survive deployment restarts, report progress in real time, and are held to mechanical quality gates — a course cannot be saved with misaligned paragraphs, a briefing cannot be saved without its term table and verified further-reading links. When a gate rejects, the agent reads the reason and revises inside the same session. The teacher sees only the finished artifact, or a clear, specific explanation of what a source could not support. This philosophy — machines check what machines produce, and prompts are never trusted as guarantees — runs through the whole system. Read Truth Layer & Mechanical Invariants for how deep it goes.In numbers
| Real courses produced | 33 (e.g. 2026 Government Work Report: 218 terms, 246 aligned sentence pairs) |
| Pre-meeting briefings | 9,000-character class, with graded bilingual term tables |
| Practice loop | 3-dimension multimodal audio scoring → automatic weak-term flashcards |
| Deployment | Production on Vercel, durable agent runtime, used by real teacher & students |
Where to go next
- Judges: start with the 评委导览 (Chinese quick guide) or the English quickstart — both include ready-to-use test accounts.
- Curious about the machinery: Architecture → Document Workshop → Truth Layer.
- Curious about the pedagogy: Philosophy.