Equora Documentation

Welcome to the Equora documentation. These pages describe the platform’s concepts, data model, research instruments, and planned developer interfaces.

Equora is a public-market intelligence platform designed to organize fragmented financial information into a structured research environment.

Equora is a public-market intelligence platform designed to organize fragmented financial information into a structured research environment.

The platform combines company fundamentals, financial statements, market activity, regulatory filings, corporate events, quantitative signals, AI-assisted research, and community analysis.

Equora is designed to help researchers move through a structured process: Discover, Understand, Analyze, Form a Thesis, Track.

Equora does not attempt to determine what users should buy or sell. Its purpose is to improve the information environment in which research decisions are made.

Equora is built on five principles that govern every product decision:

The platform is organized into six surfaces: the Company Universe (discovery), Company Intelligence (per-company research), Signals (change detection), Research (theses, timelines, comparison, watchlists, portfolios), Community (feed, reputation, challenges), and the Onchain coordination layer.

The Company Universe indexes public companies with filterable attributes across four dimensions: market capitalization segment, fundamental characteristics, market activity, and corporate activity.

Filters compose: for example, "small cap + revenue growth + insider activity" returns companies matching all three conditions.

Each company has a single research environment with tabs for Overview, Financials, Market, Capital Structure, Filings, Events, and Research.

The environment distinguishes reported data from Equora-derived data and links every figure to its source and period.

Financial statements are normalized for comparability while preserving as-reported figures. Every line item carries its original source, reporting period, filing date, and update date.

Market data includes price, volume, liquidity, and volatility measures. Volume and volatility baselines are computed over rolling 30-day windows and used for anomaly detection.

Capital structure covers shares outstanding, issuance history, buybacks, convertible instruments, and dilution capacity. Dilution capacity is derived from registration statements and existing authorizations.

Corporate events include filings, leadership changes, restructurings, and capital markets activity. Events are timestamped, sourced, and linked to affected signals.

Filings are indexed from regulatory sources and summarized by Equora AI. Each filing page shows the original document, the AI summary, and detected changes versus prior periods.

Signals answer "what changed?" — never "what should I buy?". Each signal carries a timestamp, source, severity, and evidence link.

The Equora Score is a composite research instrument across six components: Financial Strength, Market Quality, Corporate Activity, Information Quality, Risk, and Research Activity.

The Equora Score is a research instrument. It is NOT a forecast, a guarantee, or a recommendation.

A thesis is a structured document: central argument, supporting evidence, catalysts, risks, assumptions, expected timeframe, and invalidation conditions. Theses are version-controlled.

Timelines record the chronological evolution of a thesis or company: filings, signals, ownership changes, and research updates in one visual sequence.

Comparison places up to five companies side by side across ten metrics, subtly highlighting the strongest and weakest values in each row.

Watchlists surface recent events for followed companies: filings, score changes, unusual activity, and community research.

Research portfolios are hypothetical constructions used to test theses before capital. They are always labeled SIMULATED / RESEARCH ONLY.

Equora AI is a research assistant that summarizes filings, explains changes, and answers questions with references to underlying evidence.

Every answer displays its evidence: the filings, data points, and signals used to produce it. Where evidence is incomplete, the assistant says so.

Filings are summarized into structured briefs: what changed, what stayed the same, and what to watch. Summaries link to the original document sections they describe.

AI answers are constrained to platform data. The assistant cannot speculate beyond its sources, and every generated claim is traceable to a filing, metric, or signal.

AI outputs are generated from retrieved platform data, never from parametric memory alone. Retrieval scope, model versions, and evaluation results are documented and versioned.

The community feed is structured around tickers, arguments, and citations. Posts carry evidence votes, and challenges surface the best competing analyses.

Reputation measures research accuracy, evidence quality, published research, and successful theses. It is based on contribution quality — not wallet size.

Challenges are timed competitions with EQRA prizes, judged on evidence quality. Past challenges and winning research remain publicly archived.

Contributions include theses, evidence, challenges, filing analyses, and curation. Each contribution type carries a different reputation weight.

Profiles display reputation, accuracy, evidence quality, published research, successful theses, and contribution badges.

Research happens offchain. Coordination happens onchain: contributor rewards, research challenges, governance, reputation proofs, community programs, and ecosystem participation.

Equora builds its onchain coordination layer on Robinhood Chain. Equora is an independent application and is not operated, sponsored, endorsed, or affiliated with Robinhood.

Wallet connection is optional. All public market research can be browsed without connecting a wallet. Connecting enables contributor rewards, challenges, and governance.

Rewards are distributed onchain for accepted research, challenge wins, and curation work, based on evidence quality assessments.

Governance covers methodology changes, challenge parameters, and ecosystem programs. Governance participation requires EQRA and an onchain reputation proof.

EQRA is the coordination token of the Equora ecosystem. Ticker: $EQRA. Status: coming soon.

EQRA utility is deliberately restrained to coordination functions:

Advanced research instruments — historical signal archives, portfolio simulation, API access tiers — can be unlocked with EQRA. Core research remains free.

EQRA staking supports research curation: surfacing high-quality analyses and down-weighting low-evidence content.

Ongoing contributor programs reward sustained research quality with EQRA, allocated through transparent, onchain-recorded assessments.

Challenge prizes are denominated in EQRA and distributed onchain when results are verified.

EQRA holders participate in governance of methodology changes, challenge parameters, and ecosystem programs.

Equora is composed of a data ingestion layer (filings, market data, ownership), an intelligence layer (signals, scores, derived metrics), a research layer (theses, portfolios, community), and an onchain coordination layer.

Core entities: Company, Filing, Signal, Score, Thesis, TimelineEvent, Portfolio, Researcher, Challenge, Contribution. Every entity carries source, period, and update metadata.

The Equora API is a planned REST interface. The examples below are an API Preview / Planned Interface and are not yet live.

API keys will be issued per account with tiered rate limits. Wallet-linked keys unlock contributor-tier endpoints.

Planned endpoints for company data:

Planned endpoints for signals:

Planned endpoints for theses, timelines, and portfolios. Write access requires contributor reputation above a threshold.

A TypeScript SDK is planned alongside the public API, covering companies, signals, research, and onchain coordination helpers.

Every important data point includes: original source, reporting period, filing date, update date, and methodology.

Equora clearly distinguishes REPORTED DATA from EQUORA-DERIVED DATA. Example: Derived Market Capitalization = Share Price × Shares Outstanding.

Each signal type has a published definition, detection window, threshold, and false-positive handling. Signal definitions are versioned; changes are logged.

Score components are weighted composites of underlying measures. Component weights, inputs, and normalization are documented and expandable in the product.

AI outputs are grounded in retrieved platform data with citation requirements. Evaluation sets measure factual precision; results are published with each model version.

Research instruments (signals, scores, portfolios) are designed to prompt questions, not end them. Methodology is inspectable at every level of the platform.

Equora provides research tools and information and does not provide investment advice. Equora is not a broker, exchange, or custodian.

Community research is user-generated and does not represent Equora’s views. Evidence votes measure community assessment, not truth.

EQRA is a coordination token. It is not an investment product, does not confer claims on securities, and does not influence signals or scores. Token features described here are not live.

Data can be late, wrong, or misinterpreted. Signals can be noise. AI can err. Users should independently verify anything they intend to rely upon.