HypeMeter

Score the hype, show the evidence.

HypeMeter is an AI agent that fact-checks corporate claims. Paste any public claim — an IR statement, an earnings line, a press-release quote — and the agent gathers live, publicly observable web evidence through Bright Data and computes a Hype Score (0–100): the measurable gap between what a company says and what the public web actually shows. Every score links back to its sources.

Built solo in five days for the Web Data UNLOCKED Hackathon (Bright Data × NativelyAI × lablab.ai) — Track 2: Finance & Market Intelligence.

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Why

Every week, companies announce bold claims — hiring sprees, partnerships, explosive user growth. For investors and journalists, verifying a single claim against reality can take hours or days of manual digging. There is no fast way to separate substance from hype.

HypeMeter turns an analyst's week of digging into a 30-second triage — and never returns a black-box number. Every result shows its sources and its scoring method.

How it works

Claim ─▶ Gemini agent ──(Function Calling)──▶ Bright Data SERP API
                │                                   │
                │   LinkedIn Jobs · Glassdoor · Reddit · News
                ▼                                   │
        cross-reference  ◀──────────────────────────┘
                │
                ▼
        Hype Score (0–100) + linked evidence

1. A Gemini 2.5 Flash agent reads the claim and, via Function Calling, autonomously decides what to look up.
2. It queries multiple live sources through the Bright Data SERP API (LinkedIn Jobs, Glassdoor, Reddit, news), enforcing source diversity.
3. It cross-references the gathered numbers against the claim and computes a transparent Hype Score with a visible formula.

Example. Tesla's "hiring 3,000 AI engineers" claim scores 60 / Partially Supported — against 174+ observable open AI engineering roles, a real and transparent gap. It works on history too: run it on WeWork (2019) or Nikola (2020) and it flags the same gaps the market discovered far too late.

Tech stack

Layer	Tool
Web data	Bright Data SERP API — the evidence engine
AI agent	Google Gemini 2.5 Flash (Function Calling)
Frontend	Next.js (App Router) · React · TypeScript
Styling	Tailwind CSS · Framer Motion
Database	Neon (serverless PostgreSQL)
Deployment	Vercel

Getting started

npm install
cp .env.example .env.local   # then fill in the values below
npm run dev

Open http://localhost:3000.

Environment variables

Variable	Purpose
BRIGHT_DATA_API_TOKEN	Bright Data API token
BRIGHT_DATA_SERP_ZONE	Bright Data SERP API zone name
GEMINI_API_KEY	Google Gemini API key
DATABASE_URL	Neon PostgreSQL connection string
USE_MOCK_EVIDENCE	true to use mock evidence without live Bright Data calls (dev)

Project structure

app/
  page.tsx                # claim input
  result/[id]/page.tsx    # Hype Score result
  api/
    analyze/route.ts      # main agent endpoint
    evidence/route.ts     # Bright Data evidence module
lib/
  brightdata.ts           # Bright Data SERP client
  gemini.ts               # Gemini client + function definitions
  db.ts                   # Neon database client
components/               # UI
scripts/                  # demo seeding & utilities

Disclaimer

HypeMeter is a research tool. Results reflect a gap between public claims and publicly observable evidence. They are not financial advice and do not allege wrongdoing by any company.