Native Performance
Performance-critical paths run on a native acceleration layer, with automatic fallback.
The most performance-sensitive parts of the assistant — capability search, layout validation, template substitution, text chunking, and the internal event bus — run on a native acceleration layer for speed. Where the native layer isn't available, MeghaOS transparently falls back to a portable implementation, so behavior is identical either way — only throughput differs.
What gets accelerated
| Hot path | Why it matters |
|---|---|
| Capability ranking | Quickly picks the most relevant tools for a request from a large library |
| Layout validation | Sanitizes AI-generated interface descriptions fast, before render |
| Template substitution | Resolves variables in workflows and JIT output |
| Shared workflow context | Concurrent, reactive key/value store for parallel steps |
| Event bus | Low-latency delivery of internal events (e.g. proactive alerts) |
| Memory chunking | Splits documents for the memory store |
| Clipboard & screen capture | Fast, dependency-light OS access |
Automatic fallback
This is invisible in normal use — every feature works regardless. The native layer simply makes high-frequency operations faster and lighter on resources, which keeps the assistant responsive even under heavy multi-step workloads.