Bring your ideas life with the world’s first graphics compiler for AI.



Describe what you want – AI generates the data, content and code, we compile and render it on‑the‑fly giving users low latency, buttery‑smooth next-generation experiences.

Create any user interface, visual, scene, or rendered experience with stable, flawless logic at run-time. No effort, No servers, no templates, no compromises.




Our patent pending technology built for running AI generated code and data. It's a distributed compiler, code runner, and data renderer that turns human intent into live execution and visual output at run-time. No servers, no templates, no ML hallucinations. It's built to eliminate wait time for token streams, bringing reliable AI generated user experiences, every time to your client graphics processor.



📝 Declare intent, not code.

Describe the outcome in plain language — text or voice. No imperative code, no templates, no ML guessing.

🌍 One spec, every runtime.

Animation primitives are stored once in a versioned registry and referenced declaratively. At runtime, the same deterministic model is optimized against live device context and executed on the optimal runtime.

⏱️ Content arrives in human time.

Control logic is strictly separated from presentation content. AI aggressively prefetches future frames into constrained, presentation-only buffers; progression advances only on declarative conditions.

🔒 Auditable to the frame.

Every change — user action, device event, AI decision, UI update — is recorded on a single ordered timeline. Every rendered state is cryptographically hashable and retrievable.

⚡ Code as compression.

Streaming LLM token outputs are fused into secure, native code execution on the client. Multiple untrusted LLM streams converge on-device with runtime at the edge.

🤝 One verifiable timeline.

Humans, AI, and devices synchronize on a single, ordered, replayable timeline.

Intellectual Property

Sidespin Inc. Patent Applications

Patent pending (US & WIPO): Declarative Animation Engine — Deterministic, Context-Aware Rendering Across Platforms

A system that stores device-agnostic animation modules in a version-controlled registry, forms a deterministic model from a declarative specification, and optimizes rendering at runtime based on live contextual data from the target display device — selecting the appropriate runtime platform (GPU, WebGL, CSS, CPU) for each device.

  • Module registry + declarative spec: Animation primitives stored once, referenced descriptively, parametrized at model-formation time — no imperative code, no templates, no ML.
  • Context-driven optimization & runtime selection: The same deterministic model is optimized at runtime using live device context, then executed on the optimal runtime for that device.
  • Cross-platform deterministic equivalence: Identical visual results across GPU, WebGL, CSS, and CPU targets — behavior pinned to the model version, not the platform.
  • Verifiable, reconstructible execution: Natural audit trail from spec → model → context → optimization → runtime → execution enables reproducibility and compliance verification.

Patent pending (US): Temporal Interactive Runtime — Control-Content Separation with Async AI Preparation

A live, ongoing state handler that strictly separates control logic from presentation content — advancing experiences only on declarative conditions, while AI aggressively prefetches future frames and states into constrained, presentation-only buffers. Not a finite state machine: a continuous loop that runs across every device, auto-heals when context shifts, and produces a cryptographic audit trail of every frame and decision.

  • Control-content split: Progression locked to explicit rules; prepared payloads cannot hijack logic.
  • Declarative gating: Advances on render ticks via conditions — not async completion timing.
  • Aggressive safe prefetch: AI pre-renders ahead without risking early display or correctness.
  • Continuous auto-healing: When accessibility settings change, devices throttle, or networks hiccup, the runtime renegotiates instantly without divergence.
  • Replay & audit: Append-only logs with presentation-sequence indexing enable exact reconstruction.

Patent pending (US): Live Code-Data Compilation System — Distributed LLM runtime built for stability on cross-platform client hardware.

A distributed compilation system that transforms streaming LLM token outputs into secure, hardware-optimized native executables in real time on the client device — fusing code and data generated from untrusted, diverse LLM sources into a single continuous compilation that runs stably while the code and data change underneath it.

  • Distributed generation, client-side convergence: Multiple untrusted LLM streams fuse on the device, not a trusted server — cryptographic verification at the edge.
  • Temporal-state compilation for possible futures: Emits branched, forward-looking artifacts for the next likely states; runtime switches paths with zero-latency branch switching.
  • Predictive compilation via parallel runtime model: Dedicated ML model learns the compiler's runtime and environment, feeding predictions back to improve compilation over the device's life.
  • Cryptographic per-view recall: Every compilation step hash-gated — any running state restorable, auditable, replayable frame-by-frame.
  • Code as compression: Send the code that generates the data + tiny parameters instead of megabytes of tokens — reconstructs massive schemas locally at GPU speed.

The AI iteration loop everyone needs:

From intent to manifestation — describe the outcome in plain language and we make it real, instantly and everywhere. Instead of waiting for tokens, you're already moved to the next step.

📝 Speak

Express your intent in natural language—text or voice. The engine parses your request into goals, logic, and behaviors.

🔧 Assemble

A registry pipeline connects UI components, actions, and services into a deterministic, platform-agnostic specification.

📱 Render

Native clients—iOS, Android, web, desktop, or displays—bring the specification to life, adapting to context like locale, accessibility, or performance.

🔗 Sync

Multiple users can share the same session in real time, with synchronized states and collaborative flows.

📊 Observe

Structured interaction data is logged as users progress, supporting testing, auditing, and compliance requirements.

♻️ Refine

Adjust instructions instantly, roll back at any time, and iterate without redeployment—ensuring continuous improvement and trust.

The platform provides clear auditability, creating a verifiable record of how each experience is generated. This supports oversight, accountability, and compliance reporting required by frameworks such as HIPAA, SOC 2, GDPR, ISO 27001, and more.