Hey everyone, I’m a student developer working on an alternative search/intelligence interface called PLI 7.10.
The goal is to kill the SEO noise of modern search engines and the "knowledge cutoff" of standard LLMs. I’ve just implemented a "Self-Healing" logic that I’d love some architectural feedback on.
The Logic: Instead of the AI simply saying "I don’t know" when asked about recent events (e.g., Luke Littler’s 2026 stats), the backend now detects the failure and auto-triggers a @data layer. It fetches, translates (via Google API), and ranks Wikipedia + YouTube context in one loop.
Tech Specs & Trade-offs:
Stack: Next.js / Node.js / Vercel.
Latency: It’s about 20% slower than a standard hallucinating chat, but the accuracy for "live" da…
Hey everyone, I’m a student developer working on an alternative search/intelligence interface called PLI 7.10.
The goal is to kill the SEO noise of modern search engines and the "knowledge cutoff" of standard LLMs. I’ve just implemented a "Self-Healing" logic that I’d love some architectural feedback on.
The Logic: Instead of the AI simply saying "I don’t know" when asked about recent events (e.g., Luke Littler’s 2026 stats), the backend now detects the failure and auto-triggers a @data layer. It fetches, translates (via Google API), and ranks Wikipedia + YouTube context in one loop.
Tech Specs & Trade-offs:
Stack: Next.js / Node.js / Vercel.
Latency: It’s about 20% slower than a standard hallucinating chat, but the accuracy for "live" data is significantly higher.
Data Source: Uses a multi-language Wikipedia ranker to find the most "dense" info regardless of the user’s language.
Current Hurdles:
Vercel Cold Starts: The multi-step scraping/translation layer is hitting some latency on the first hit.
UX: Does a "3+1" card layout (Wiki + Video context) feel intuitive for a dev-tool, or is it too cluttered?
Link: https://pli7.vercel.app/