HyperTalk is a voice-first interface where intent drives layout. Speak naturally — the system infers what you need, orchestrates the UI, and renders it as a dynamic spatial canvas.
No menus. No buttons. No screen to learn. Say what you want and the interface materializes around your words.
Intent → Layout, not command → layout.
Voice-first isn't a design preference — it's an accessibility architecture.
HyperTalk removes the assumption that users can see, tap, or navigate complex visual hierarchies. The spatial canvas adapts to the user: high-contrast cards for low vision, paged content for screen readers, voice-only operation for hands-free use.
Every interaction that works by voice also works for users who need it to. The interface meets people where they are.
Traditional interfaces require you to learn their structure — where the buttons are, what the menus contain, how to navigate between views. Voice assistants replaced buttons with commands but kept the same rigid structure underneath.
HyperTalk removes the indirection entirely. You express intent; the system infers the right layout, content density, and interaction mode — then renders it as cards on a spatial canvas you control with your voice.
Voice input flows through a layered architecture that separates intent inference from UI rendering — making the system predictable, testable, and fast.
Micro-commands like "scroll down," "turn the page," and "go back" execute locally in under 100ms — no LLM round-trip. Rule matching, then a tiny on-device classifier, with LLM fallback only when confidence is low.
Natural speech becomes structured intent objects — goal, content type, layout mode, density, and interaction style. The system infers "show me a summary of today's news" as a reading-mode, fullscreen, summary-density news feed.
Deterministic rules map intent objects plus current context to UI commands. The same intent with the same context always produces the same layout. No inference at the rendering layer — only execution.
UI commands flow over NATS to the SwiftUI client, which updates the spatial canvas. Commands are idempotent and replayable — the system can recover from disconnections without losing state.
Intent objects — structured, validated, deterministic
Local micro-commands — sub-100ms, no network dependency
Deterministic orchestration — same input, same layout, every time
Idempotent commands — replay-safe, crash-recoverable
LLM-generated UI — unpredictable, untestable layouts
Command-driven voice — "open app, tap button" with extra steps
Stateless rendering — no context means no adaptation
Every voice input becomes a validated intent object that captures what the user wants — not what buttons to press.
Intent objects carry goal, mode, focus, density, interaction style, and extracted entities. Each field has a defined enum — no free-form strings reaching the UI layer.
Intent inference considers the active mode, current card, available actions, user profile, and the last three intents. "More detail" means different things in a news feed vs. a data table.
When intent can't be determined, the system emits a "clarify" intent rather than guessing. The UI prompts naturally — no error dialogs, no dead ends.
Information density adapts to the conversation. Start with summaries; say "more detail" and the same content expands — without navigating to a different view.
intent: request_news, mode: reading, focus: fullscreen, density: summary
HyperTalk renders content as typed cards on a spatial canvas. Each card has a validated schema, deterministic rendering rules, and voice-controllable interactions.
The canvas is voice-controlled at every level. "Scroll down" moves within a card. "Next card" shifts focus. "Fullscreen" expands the active card. "Split view" arranges two cards side by side. Layout adapts to content — a chart card alongside a data table, a news feed filling the screen.
"This doesn't look right" triggers a diagnostic flow: the system captures a screenshot, sends it for analysis, and returns a focused diagnosis card — all by voice. No manual screenshots, no filing tickets, no describing the problem in text.
The diagnosis card appears fullscreen with an "Analyzing…" state that resolves into structured findings. The system sees what you see and tells you what's wrong.
HyperTalk connects to the services you use daily — rendering them as cards on the spatial canvas, controllable entirely by voice.
OAuth-backed Gmail and Outlook. Threads render as conversation cards with voice-driven triage.
Business Cloud API integration. Messages render as chat cards with threaded reading mode.
OAuth playback control. Now Playing card with album art, track info, and voice controls.
HyperTalk is built in pure Swift and SwiftUI — a native Apple experience with ADAMAS providing the agent intelligence layer.
Built entirely in Swift with SwiftUI — platform-native accessibility, system integration, and the polish expected of an Apple-ecosystem product. Runs on iOS and macOS.
Fast, accurate speech recognition that converts voice input into text for intent inference. Low-latency transcription that keeps the voice interaction feeling immediate and natural.
Natural voice synthesis that delivers responses with appropriate pacing and clarity. The voice layer that makes the system feel like a conversation, not a text-to-speech readback.
Intent inference, content retrieval, and integration orchestration run on ADAMAS — providing durable execution, knowledge graph memory, and multi-agent coordination.
adamas.network →HyperTalk is currently in development for iOS and macOS, with the spatial canvas engine, intent architecture, and voice stack coming together as a native Apple experience.
If you're interested in voice-first interfaces, accessibility-driven design, or the future of how humans interact with AI — we'd like to hear from you.