Cross-language chat
Buoychong pairs English ↔ Mandarin teammates. GlyphIR keeps turns aligned so summaries, replies, and trails stay in sync across languages.
EarthCloud defines a shared format (GlyphIR) for meaning: messages, intents, roles, and trails—across languages, models, and apps.It keeps what was said, what it means, and where it lives aligned for every system that touches it.
Part of the Funwae ecosystem.
Used with Glyphd Labs, Buoychong, and Tongbuku.
GlyphIR is the envelope that keeps surface text, normalized meaning, context links, and quality metadata together—so any model or app can reason over the same intent.
Meaning core
GlyphIR
Spec status
Draft v0.1
Definition · Canon
EarthCloud is the meaning layer for multilingual AI: an open specification (GlyphIR) that captures surface text, normalized meaning, participants, context links, and provenance so every system sees the same intent.
Where people use it
EarthCloud shows up anywhere you need consistent meaning across languages, channels, or agents. Here are a few places it is already working.
Buoychong pairs English ↔ Mandarin teammates. GlyphIR keeps turns aligned so summaries, replies, and trails stay in sync across languages.
Cross-border product teams capture decisions as structured GlyphIR turns, then write them to Tongbuku for replayable audits.
Docs assistants emit GlyphIR so intent, topic, and stance are searchable—no matter which model produced the answer.
Funwae worlds and on-site kiosks use GlyphIR to hand conversations between characters, agents, and visitors without losing context.
GlyphIR overview
EarthCloud doesn't decide what the model should say—it describes what was said, what it means, and how to connect it to the rest of your stack. GlyphIR keeps these layers bundled so every service interprets the same envelope.
Original utterance, language, script, and any normalization hints so text can be reconstructed faithfully.
Intents, entities, topics, sentiment/stance—structured in a way models and tools can reason over.
Who spoke, who was addressed, which agents or tools are in the loop, plus their tone/register preferences.
References to threads, rooms, worlds, Tongbuku trail IDs, message IDs, and related turns.
Confidence scores, model or human provenance, translation quality hints, and safety annotations.
Implementers can extend this shape, but the contract stays the same: surface text, normalized meaning, participants, context links, and quality metadata share one envelope. Trails (via Tongbuku or your own log) simply point back to these IDs.
{
"glyphir_id": "gph_01HX...",
"surface": {
"text": "请帮我把这段内容总结一下给同事",
"lang": "zh-CN",
"source_lang": "en"
},
"meaning": {
"intent": "summarize_content",
"entities": [{ "type": "person", "name": "Chinese colleague" }],
"stance": "helpful"
},
"participants": {
"speaker": { "role": "user", "card_id": "chatcard_875" },
"audience": ["teammate"]
},
"context_links": {
"trail_id": "trail_8734",
"room": "funwae/product-design"
},
"quality": {
"confidence": 0.91,
"source": "llm:glyphd-2025-03"
}
}Stack placement
EarthCloud (GlyphIR) is the semantic layer. It pairs with ChatCard for identity, Tongbuku for trails, and the broader Funwae tools for how those conversations show up in the world.
Defines who is speaking, identity preferences, and provider context before a turn becomes GlyphIR.
Captures the meaning layer: surface text, normalized intent, participants, context links, and provenance.
Stores append-only trails that reference GlyphIR IDs so every turn is auditable and replayable.
Places where people experience the conversation layer—cross-language chat and shared worlds.
Templates, personas, and OS-level execution that apply styles to GlyphIR-driven actions.
Questions
Contact
EarthCloud is for teams who care about cross-language collaboration, structured meaning, and real trails—not just prompts and logs. If that's you, we'd love to hear from you.
Contact: info@earthcloud.co