Find the trend before the market does.

Insider-flow signal — what informed, access-rich actors are trading, structured for signal extraction, not just raw disclosures.

• GET/v1/congress/trades

  Disclosed House & Senate trades, filterable by member, ticker, party, and filing date — the raw substrate for an informed-flow factor.

• GET/v1/congress/trades/{id}

  A single disclosure with STOCK Act filing metadata and disclosure lag, to model the delay between the trade and when the market saw it.

• GET/v1/congress/members

  Roster of all 535 members with disclosure history and committee assignments, so you can weight signal by seat and sector oversight.

• GET/v1/congress/members/{id}/trades

  Full trade history for one member — build per-actor track records and conviction weights.

• GET/v1/congress/committees/{id}/activity

  Trading activity rolled up by committee, aligning flow with the sectors a committee actually oversees.

• GET/v1/congress/signals/insider-flow

  Pre-computed insider-flow score per ticker — a drop-in feature ranking names by informed-actor accumulation.

Influence-flow signal — map corporate influence spend to sector and price exposure before the thesis is consensus.

• GET/v1/lobbying/filings

  LDA lobbying filings by registrant, client, issue area, and quarter — where policy money is moving and which issuers are exposed.

• GET/v1/lobbying/filings/{uuid}

  One filing in full, with issues lobbied, lobbyists, and reported spend.

• GET/v1/lobbying/clients/{id}

  Spend history and issue exposure for a single client, ready to join against your position book for a policy-risk overlay.

• GET/v1/lobbying/top-spenders

  Leaderboard of influence spend by client and sector over a window — spot ramps early.

• GET/v1/lobbying/issues/mix

  Breakdown of spend by issue area, so you can tilt toward the policy themes gaining budget.

• GET/v1/lobbying/registrants/{id}

  Activity for a lobbying firm across its client book — a cross-issuer influence network view.

• GET/v1/lobbying/signals/policy-exposure

  Per-ticker policy-exposure score blending spend, issues, and contract adjacency into one feature.

Political-capital signal — who funds whom, tied back to the sectors and issuers with the most at stake.

• GET/v1/fec/contributions

  Itemized contributions filterable by contributor, committee, cycle, and employer — map corporate and executive giving.

• GET/v1/fec/committees/{id}

  A committee’s receipts, disbursements, and affiliations over a cycle.

• GET/v1/fec/candidates/{id}/funding

  Funding profile for a candidate — sector concentration and top backers.

• GET/v1/fec/signals/sector-giving

  Net political giving by sector as a directional signal on regulatory posture.

Revenue-visibility signal — federal award flow mapped to publicly traded recipients, ahead of guidance.

• GET/v1/contracts/awards

  Awarded federal contracts filterable by recipient, agency, NAICS, and date — mapped to public parents.

• GET/v1/contracts/recipients/{id}

  Award history for one recipient — backlog and momentum for an issuer.

• GET/v1/contracts/agencies/{id}/spending

  Spending by agency and program, to anticipate which vendors benefit.

• GET/v1/contracts/signals/award-momentum

  Per-ticker award-momentum score — acceleration in federal revenue exposure.

Consensus & odds signal — real-money probabilities for the events your positions are exposed to.

• GET/v1/predictions/markets

  Live and historical prediction markets by topic and status — a real-money probability for each event.

• GET/v1/predictions/markets/{id}

  One market with current odds, liquidity, and resolution criteria.

• GET/v1/predictions/markets/{id}/history

  Point-in-time odds series for a market — the input to event-driven backtests.

• GET/v1/predictions/consensus

  Aggregated consensus probability across correlated markets for a theme.

• GET/v1/predictions/movers

  Markets with the largest odds moves over a window — where conviction is shifting fastest.

The signal layer — news structured, entity-tagged, and semantically linked to tickers, events, and odds so headlines become machine-usable features.

• GET/v1/news/search

  Semantic news search over structured, deduplicated articles — retrieve by meaning, not keywords.

• GET/v1/news/{id}/entities

  Entities resolved from one article to tickers, people, and issues — build per-name news-flow features.

• GET/v1/news/{id}/related-markets

  Prediction markets and securities an article is semantically linked to, with confidence scores.

• GET/v1/news/signals/odds-moves

  News items time-aligned to the odds moves they preceded — a news→consensus lead signal.

• GET/v1/news/sentiment/by-entity

  Rolling entity-level sentiment derived from structured news flow.

The price layer — the series you regress every other signal against, plus composite and correlation features.

• GET/v1/markets/quotes

  Reference and end-of-day market data for a symbol universe — the price series behind every feature.

• GET/v1/markets/signals

  Composite Ezana signals blending the datasets above into a single score per name.

• GET/v1/signals/correlations

  Discovered relationships between obscure datasets and price — the non-obvious links you can trade around.

• GET/v1/signals/backtests/{id}

  Point-in-time backtest results for a signal spec, with disclosure lag preserved so history isn’t contaminated by hindsight.

The signals that only exist because we hold all seven dimensions at once — joins across influence, capital, and consensus that no single-vendor feed can reconstruct.

• GET/v1/cross/influence-to-capital

  Aligns lobbying and campaign-finance spend (Capitol Watch) against subsequent institutional accumulation (Titans Shadow) per issuer, surfacing names where influence money leads the smart money.

• GET/v1/cross/contract-to-insider

  Joins federal contract-award momentum (Capitol Watch) with corporate insider buying (Titans Shadow) on the awarded issuer, flagging where the people closest to the win are also buying.

• GET/v1/cross/policy-to-price

  Maps bill progression and agency rulings (Regulatory Winds) onto the sector baskets they move (Titans Shadow prices), scoring each ticker by unrealized regulatory catalyst.

• GET/v1/cross/consensus-vs-fundamentals

  Contrasts prediction-market odds (The Hive) with the fundamentals and analyst path (Titans Shadow) for the same event, isolating where crowd conviction diverges from the sell-side.

• GET/v1/cross/demand-to-guidance

  Regresses consumer demand signals — search, web traffic, card spend (Consumer Whispers) — against forward guidance and revisions (Titans Shadow) to catch demand inflections ahead of the print.

• GET/v1/cross/macro-regime-overlay

  Tags every other signal with the prevailing macro and geopolitical regime (Global Empire Lighthouse) so a factor can be conditioned on the environment it actually works in.

• GET/v1/cross/composite/{ticker}

  One call returns a per-ticker rollup of every cross-dimensional signal above, weighted and decayed by disclosure lag — a drop-in composite feature.

Time-structured relationships between dimensions — which trend leads which, by how long, and when the usual link breaks.

• GET/v1/relationships/lead-lag

  Estimated lead-lag between any two dimension series for a ticker or sector (e.g. patent momentum → price), returning the lag in days and the strength of the relationship.

• GET/v1/relationships/divergence

  Flags where two normally-correlated dimensions have decoupled — insider selling into rising retail sentiment, say — ranked by how far the pair has drifted from its historical link.

• GET/v1/relationships/confirmation

  Counts how many independent dimensions currently agree on a name, turning multi-source corroboration into a single conviction score.

• GET/v1/relationships/network/{entity}

  Returns the influence graph around an entity — the politicians, lobbyists, contractors, and institutions linked to it across dimensions — for second-order exposure mapping.

• GET/v1/relationships/regime-shift

  Detects the moment a cross-dimensional relationship structurally changes, so you can retire or re-weight a factor before it quietly stops working.

• GET/v1/relationships/backtest

  Point-in-time backtest of any relationship above with disclosure lag preserved, so a lead-lag edge is measured on the data you would actually have had.