Show HN: I'm 16 and building an AI based startup called Factful with friends

Original Article ↗ Hacker News Discussion ↗

Product concept & current capabilities

  • Web app for checking factual accuracy plus grammar/writing quality.
  • Currently uses an OpenAI-based backend; team plans a custom LLM specialized for “text fitting” later.
  • Fact-checking is intended to work via multiple non-LLM models that:
    • Detect factual claims vs non-facts.
    • Extract queries and search trusted databases/APIs (e.g., Google Fact Check, curated corpora).
    • Feed retrieved evidence into an LLM that rewrites text using “known good” data.
  • In the beta, this full pipeline is not yet implemented; a simplified version is deployed to test scale, bugs, and security.

User experience & technical issues

  • Multiple users report errors, timeouts, or “nothing happens” on “Check Everything” / “Fact Check.”
  • There is/was a global 1-request-per-second limit, causing failures under HN traffic.
  • App was briefly trying to connect to a Vite dev server in production; dev-mode remnants noted.
  • Some suggestions are overlong, off-topic, or UI-clipped; requests for a clearer, one-click “correct sentence” option.
  • Bugs include naive text replacement (wrong number substitution) and strange factual edits.

Effectiveness & limitations of LLM fact-checking

  • Many commenters doubt LLMs can serve as reliable fact checkers due to:
    • Training on mixed-quality web data.
    • Hallucinations and lack of calibrated uncertainty.
  • Others propose mitigations: RAG over Wikipedia or curated sources, mandatory citations, mechanisms for expressing uncertainty, ensemble methods, and constrained outputs (function calling / yes–no answers).
  • Several test cases show both successes (catching recent political news details) and clear failures (physics examples, joke prompts, history fuzziness).

Business model, legal setup & API

  • Service is currently free; goal is to stay free as long as possible and later be cheaper than competitors.
  • For businesses: planned per-query API pricing and per-user subscriptions.
  • Company is incorporated in the UK because that jurisdiction allows 16-year-old founders.
  • API and some business features are planned for summer, after school exams.

Ethical/scope debate & general advice

  • Strong debate over whether “misinformation elimination” is even solvable, or desirable at web scale.
  • Suggestions to focus on narrow, objective domains first and to emphasize human error reduction and writing aid.
  • Many commenters are encouraging about the initiative and learning value, while urging realism about technical and societal limits.