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6/10

ClaimCheck

An AI email and document reviewer for consultants, executives, lawyers, and students that runs an adversarial verification pass on every draft — checking the math, double-clicking the numbers, hunting for hallucinated citations, and forcing the model to prove each claim before it ever reaches the recipient.

Target user

Management consultants, investment-banking analysts, and senior executives who send high-stakes memos

Features
  • Adversarial verification pass that flags every numeric claim, citation, and named entity against the source documents and marks confidence
  • 'Show your work' inline footnotes so the recipient can see exactly which sentence you verified and which you didn't
  • Tone, audience, and counterparty-aware rewrite suggestions (board memo vs. client email vs. regulator filing)
  • Works against pasted text, attached PDFs, and live email drafts in Gmail/Outlook
Why now

Loom-kit's framing of 'agents that guess versus agents that verify' maps directly onto the exec's daily fear: an AI-drafted memo with one wrong number costs a career. Non-technical professionals need this adversarial pattern more than engineers do.

Signals · overall 6/10
Demand
7/10

Forrester cites AI hallucinations costing $67.4B in 2024 with 47% of executives making major decisions on unverified AI output; legal hallucination rates hit 18.7% and 1,174+ court cases involve AI-fabricated citations — exact fear profile for the target user of high-stakes outbound memos.Thomson Reuters: Accuracy in AI: Reducing hallucinations at workBest AI Hallucination Detection Tools 2026

Whitespace
5/10

Clarity already runs adversarial multi-model verification ('Rivalry Engine') for legal/medical/financial content, Veru/AICitationChecker attack the citation-narrow space, and Hebbia/V7 Go/AlphaSense own the analyst desk — the broad 'verify before sending' shell is contested; only the specific email-outbound-for-execs wedge remains narrower but is not uncontested.Clarity AI Hallucination CheckerHebbia: AI in Investment Banking Use Cases

Monetization
7/10

Proven willingness to pay: Clarity charges $20/~10 review sessions ($5 top-ups), Enterprise per-seat models exist, and ROI math is explicit (a single fabricated legal citation risks $31K Rule 11 sanctions vs pennies of verification) — buyers in consulting/IB already pay $1K+/seat/mo for Hebbia-style tooling.Pricing and ROI of AI Hallucination Detection Tools10 Best AI Tools for Investment Banking [2025]

Longevity
8/10

Need strengthens as AI output volume grows and regulators (SEC, bar associations, EU AI Act) tighten liability — error-cost asymmetry is structural, not cyclical, so verification becomes a permanent layer of professional AI use.Thomson Reuters: Accuracy in AI

Feasibility
5/10

Adversarial multi-model review is technically validated (Clarify's Rivalry Engine is a working precedent) but combining reliable math-check + citation-verify + Outlook/Gmail hookup for non-technical users is meaningfully more engineering than a wrapper; the cited .claude-skills repo targets coding agents, a partial fit at best.Clarity AI Hallucination Checker

33 battle-tested skills + minimal .claude harness for any coding agent (Claude Code, Cursor, Codex, Gemini CLI). · ★ 152GitHub Trending · 2026-07-05 (20d ago)