SiteAsk is the productised version of the Ask Amit assistant on this site — generalised so any blog, docs, or marketing site can install it with a single script tag. The widget loads a static prebuilt index, runs query embedding in the visitor's browser via Transformers.js (all-MiniLM-L6-v2 q8), does cosine retrieval locally, and only then POSTs to a tiny user-supplied backend that proxies the LLM call. That architecture lets it undercut SaaS competitors (Inkeep, Kapa.ai) on cost: no embedding-API bill, no vector DB to host, you pay only for LLM calls and only when someone actually chats. Ships as @siteask/widget (the embed bundle) plus a Node CLI for building the index from markdown directories or arbitrary URLs.
~10 KB gzipped widget bundle; transformers.js + model lazy-load only when a visitor opens the chat
Site owners pay only for LLM tokens, never for embedding API calls or vector DB hosting
One-script-tag install with sensible defaults; programmatic SiteAsk.init() for advanced users
AI-powered job search platform: discover roles, evaluate fit, tailor applications, and close skill gaps. One-time pricing, no subscriptions.
View ProjectAn installable Model Context Protocol server that exposes my blog posts as queryable resources, tools, and prompts to any MCP-compatible AI client.
View Project