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Scoring Methodology

TL;DR: How We Rank AI Companies

Rankings are calculated from 5 dimensions, weighted by time-decayed event activity: Innovation (25%), Adoption (25%), Market Impact (20%), Media Attention (15%), and Technical (15%). Rankings update every 5 minutes based on real-time data from Reddit, arXiv, GitHub, and tech news. Sentiment and Hype/Reality are tracked separately as supplementary signals.

How does Sector HQ rank AI companies?

Rankings are calculated from 5 dimensions, weighted by time-decayed event activity: Innovation (25%), Adoption (25%), Market Impact (20%), Media Attention (15%), and Technical (15%). Rankings update every 5 minutes based on real-time data from arXiv, GitHub, Reddit, and tech news. Sentiment and Hype/Reality are tracked separately as supplementary signals.

This methodology focuses on real activity (product launches, research papers, code releases) over marketing hype. Events are scored with time decay (recent events count more) and source diversity multipliers.

Overview

We track real AI activity across companies - not just press releases and marketing hype. Our scoring system evaluates five core dimensions (Innovation, Adoption, Market Impact, Media Attention, Technical) to separate companies that are actually shipping from those just talking about it.

Rankings update every 5 minutes as new events are detected. Events decay exponentially over time (10% per week), giving more weight to recent activity. We use AI-powered quality filtering and pattern analysis to ensure only meaningful activity affects scores.

Scoring Dimensions

Our ranking engine scores events across five dimensions. Each event contributes to the company's overall score through time-decayed, source-diversity-weighted aggregation:

1. Innovation

Weight: 25%

Measures new products, breakthrough announcements, and novel capabilities:

  • Product launches - new models, tools, and platform features
  • Breakthrough announcements - novel capabilities and state-of-the-art results
  • Creative applications - unique use cases and integrations

2. Adoption

Weight: 25%

Tracks user adoption signals and integration growth:

  • User growth - adoption milestones, platform usage metrics
  • Integration announcements - third-party platform support
  • Developer ecosystem - SDK adoption, API usage, community tools

3. Market Impact

Weight: 20%

Evaluates industry influence and business momentum:

  • Funding rounds - investment activity and valuations
  • Partnerships - strategic alliances and collaborations
  • Acquisitions - M&A activity and market consolidation

4. Media Attention

Weight: 15%

Measures press coverage and industry discussion:

  • News coverage - tech press, mainstream media mentions
  • Community discussion - Reddit, Hacker News, developer forums
  • Industry events - conference talks, keynotes, demos

5. Technical

Weight: 15%

Evaluates research output and engineering capabilities:

  • Research papers - arXiv publications, peer-reviewed research
  • Technical capabilities - benchmarks (MMLU, HumanEval, etc.)
  • Open source - GitHub activity, code releases, documentation

Time Decay & Source Diversity

Events are weighted by recency and source diversity:

  • Time Decay: Recent events count more — older events lose weight exponentially
  • Source Diversity: Scores from multiple independent sources are weighted higher than single-source signals

Supplementary Metrics

These are tracked separately and do not affect ranking scores:

  • Sentiment: Community perception analysis (displayed on company pages)
  • Hype/Reality Gap: Marketing claims vs actual technical output
  • Event counts: Raw 7-day and 30-day event volumes

How Scoring Works

Each event is classified across 5 dimensions (Innovation, Adoption, Market Impact, Media Attention, Technical), then aggregated with time decay and source diversity weighting:

Score = Σ[(Innovation × 25% + Adoption × 25% + Market Impact × 20% + Media × 15% + Technical × 15%) × Time Decay × Source Diversity]

We apply AI-powered quality filters, time decay (recent events count more), and source diversity multipliers to ensure scores reflect genuine AI progress rather than marketing noise.

Update Frequency: Rankings update every 5 minutes. Event detection varies by source (RSS ~15min, Reddit ~30min). Sentiment is calculated per-event (instant). Hype Gap updates every 5 minutes (requires minimum 3 events for accuracy).

What We Track

✅ Real Activity

  • → Product launches with actual demos
  • → Research papers on arXiv/journals
  • → GitHub activity and code releases
  • → Substantive partnerships
  • → Validated funding rounds
  • → Hiring/layoffs (market signals)

❌ Marketing Noise

  • → Vague press releases
  • → "Exploring AI" announcements
  • → Repackaged old news
  • → Executive quotes about strategy
  • → Generic AI blog posts
  • → Marketing without product

Our Principles

  • All companies evaluated with identical criteria - no special treatment
  • Rankings cannot be bought or gamed - we track what's actually happening
  • Updates every 5 minutes based on fresh data from multiple sources
  • High-level methodology shared publicly, implementation details proprietary

Last updated: 2/17/2026