The Story Behind SMS AI
A lot of general AI frontends have notable latency issues when streaming code blocks or rendering markdown. I wanted to see if I could optimize the processing structure to bring the time-to-first-token down under 100ms.
SMS AI is a lightweight, edge-delivered multimodal workspace built to handle text generation, code refactoring, and document compilation without the usual lag.
Engineering & Key Features
• Low-latency streaming: Custom routing layers keep the time-to-first-token under < 100ms.
• Code execution & syntax rendering: Generates, refactors, and explains code arrays in standard languages (C++, Python, JS, etc.) with clean syntax highlighting.
• RAG & Context Parsing: Supports direct uploads of heavy files (.pdf, .docx, .txt) to isolate data strings and extract instant contextual summaries.
• Live Web-Aware Search: Features a web-retrieval module that crawls live data layers and appends exact source citations.
• Platform Stability: Built on redundant infrastructure maintaining a stable 99.99% uptime profile.
System Architecture Preview
Current Infrastructure Allocation
The system is open for production testing:
• Free Plan ($0/mo): 10 daily streaming chat messages. No account setup or registration required to test the core logic.
• Pro Plan ($20/mo): Unlimited processing queues, priority model speeds, and raw CSV data export formats.
The project was fully deployed by ~M_Sameer. If you spot any edge-case bugs, latency drops, or parsing issues, drop a comment below. I am actively tuning the performance profiles.
Thanks for taking a look.