AIRE Algo Readability Score
AxonIR's NLP scoring engine measures how well reAlpha Tech Corp.'s SEC filings communicate with the 70% of trading volume that is algorithmic. Get a free benchmark report covering Fog index, sentiment polarity, litigious-language density, and peer comparison.
What is algo readability?
Algo readability is a 0–100 composite score measuring how well an SEC filing or press release communicates with algorithmic traders, who account for roughly 70% of US equity volume. AxonIR's NLP scoring engine evaluates six dimensions: Gunning Fog index, litigious-language density (Loughran-McDonald), sentence complexity, sentiment polarity, forward-looking-statement clarity, and entity recognition. A higher score means algos can extract investment-relevant signals from your disclosure faster — which translates to tighter spreads, deeper liquidity, and reduced volatility around filing events.
Why AIRE matters
- Company
- reAlpha Tech Corp.
- Sector
- Real Estate
- Exchange
- NASDAQ
- Market Cap
- ~$33M
reAlpha is an AI-driven real estate technology company on NASDAQ. As a sub-$100M micro-cap, AIRE faces the classic small-cap visibility problem: 70% of trading volume is algorithmic, and most algos cannot read complex real estate disclosure language without an explicit readability score. AxonIR scores AIRE every quarter against real-estate-pubco peers.
Get your free AIRE algo readability report
No credit card. 5-business-day delivery. Includes peer benchmark, top-3 readability fixes, and a section-by-section sentiment heatmap.
Request Free Report for AIREAIRE algo readability — sector framing
Real Estate pubcos face sector-specific disclosure patterns that algorithmic traders weight differently than generic NYSE/NASDAQ filings. For real estate operating companies, the most-watched language elements are revenue-recognition disclosures, segment-result narratives, forward-looking-statement risk hedges, and any mention of strategic alternatives.AxonIR's NLP engine is calibrated to those sector-specific patterns and reports AIRE's scores against the relevant peer set rather than a generic universe.
AIRE peer comparison
Algo readability is a relative metric. A score of 72/100 means little in isolation — what matters is whether AIRE is above or below its peer median, and which dimensions drag the composite down. AxonIR provides peer-benchmarked scoring against real estate micro/small-caps under $500M market cap, with quarterly recalibration so AIREcan track movement against the right comparables rather than a stale benchmark.
How AIRE can act on its score
Improving an algo readability score is mostly about disclosure-language hygiene, not strategy changes. AxonIR's reports surface the highest-leverage edits: which paragraphs in the 10-Q, 10-K, and 8-K drag the Fog index up, where litigious-language density spikes, which forward-looking statements lack the algo-readable safe-harbor language, and which sentences run long enough to crash sentence-complexity scoring. Each issue maps to a specific 1–3 sentence rewrite. AIRE's next filing should ship with a measurably higher composite score, and the report explains exactly why.