Find the answers you are looking for. Qeeebo is a next-generation question-and-answer website with a bold, singular goal: to become one of the largest curated Q&A platforms in the world.
Live Beta v0.4: https://qeeebo.com/
How did you come up with the idea behind your submission?
Qeeebo emerged from repeatedly encountering the same problem while building and researching with AI: answers were fragmented across forums, blogs, and LLM outputs, with no durable, citable, or indexable source of truth. Search engines increasingly return synthesized summaries without clear provenance, while AI models hallucinate or paraphrase without stable URLs. Qeeebo was designed as an inversion of that model—rather than generating answers on demand, it pre-builds and publishes canonical question-answer pages at massive scale, each with a permanent URL, structured data, and human-readable context. The goal is to create an internet-native reference layer optimized for both humans and machines, where answers exist first as durable web objects, not ephemeral responses.
Show the cool parts of your product: what differentiates it?
Qeeebo’s differentiation lies in its scale-first, citation-first approach. Instead of treating search as the primary product, Qeeebo treats the answer itself as the atomic unit—each question becomes a standalone, indexable page with consistent structure, schema, and semantic clarity. The platform is designed to host tens to hundreds of millions of answers without requiring a traditional database or runtime backend, making it fast, resilient, and inexpensive to operate. This enables near-instant global delivery via CDN, predictable URLs that AI systems can cite reliably, and long-tail coverage that conventional editorial or dynamic systems cannot economically achieve. In practice, Qeeebo behaves more like a static “answer graph” than a website.
Explain some architecture and design of the submission!
Qeeebo uses a fully static architecture built around large-scale content sharding, deterministic URL generation, and offline preprocessing. Questions and answers are generated or curated in batch, stored as structured JSON, deduplicated globally, and converted into Markdown with strict front-matter and schema consistency. Pages are organized into hashed directory trees to avoid filesystem bottlenecks and allow parallel builds, then rendered into static HTML using segmented builds rather than full site rebuilds. Search is handled client-side using precomputed indexes, while discovery relies on exhaustive sitemaps and predictable taxonomy pages. The result is a system that scales horizontally with storage and bandwidth rather than compute, making it viable to publish and serve orders of magnitude more content than traditional dynamic platforms.
We have obviously also used Groq fundamentally in creation of Questions and Answers, after using 20+ different models and services, Groq stood out as the seamless solution that helped us scale now to over 100 million questions (for our main launch soon!). Groq batching of queries not only saved us cost but also was very efficient. We utilized scripting to interact with the batch system via command line which automated everything. We would love some swag! 
And perhaps to expand further in a case study some of the technical details of how Groq propelled us in a very short time to launching Qeeebo.