AskRight: Concise AI Answers with Honesty Scores
A consumer AI chat that gives you a direct answer, an honesty score for that answer, and a confidence flag when it's about to ramble — so you stop over-reading 800-word responses.
students, professionals, and curious adults who use AI assistants daily and hate the bloat
- One-paragraph default answer with optional 'expand for detail' instead of long CoT dumps
- Honesty score on each response flagging uncertain claims with sources
- Stagnation alarm: warns you when the AI is repeating itself or stuck in a loop
- Receipt mode that logs every answer with sources for citation in essays or reports
Research like PUMA confirms reasoning models routinely 'overthink' — students and pros are paying compute and time tax for answers that should be two sentences.
Verbosity is a recognized pain point ('194-Comment Revolt Against ChatGPT's Wall-of-Text Disease', LeadDev finding AI assistants are ~2x more verbose than Stack Overflow) but ranked outside top complaints in 500-post Reddit analysis (memory 34%, price 22%, context 19%).The 194-Comment Revolt Against ChatGPT's Wall-of-Text Disease ↗AI coding assistants are twice as verbose as Stack Overflow ↗
AI assistant space is saturated — ClickUp lists 20 ChatGPT alternatives, Lindy lists 15 — and no direct 'honesty-score + conciseness' competitor surfaced, but incumbents (ChatGPT, Claude, Perplexity) can add conciseness controls natively.20 Best ChatGPT Alternatives in 2026 (Free & Paid) ↗I Tested 15 ChatGPT Alternatives. These Are The Best in 2026 ↗
Consumer AI subscription market is ~$12B with 35M paying ChatGPT users, proving WTP for AI wrappers, but a consumer 'concise answer' wrapper is a thin differentiator vulnerable to free native settings.Who's Actually Paying for AI: The $12.0B Consumer Subscription Market ↗
PUMA research confirms reasoning-model overthinking is a structural issue, giving the niche legs — but OpenAI/Anthropic/Google can ship conciseness sliders natively, eroding a standalone wrapper's moat within 1-2 years.Is Your Model Thinking or Just Stagnating? PUMA ↗
A thin wrapper around existing LLM APIs with a 'be concise' system prompt and self-evaluated honesty/confidence flags is technically trivial to build in days; the 'honesty score' is the only novel piece and even that is just LLM self-scoring.