Wiseek AI

What Wiseek AI is

Wiseek AI is the analysis stack that powers every article on Wiseek. It is not a generic chatbot answering arbitrary questions over financial data — it is a focused pipeline that ingests SEC filings and licensed financial news, applies Wiseek's proprietary scoring rubric, and outputs four pieces of structured analysis per event: an importance score (1–10), a sentiment label, a plain-English summary, and a list of discrete key events extracted from the source.

The system is built around three coordinated layers: an importance scorer calibrated on historical filing-and-market-reaction data, a Wiseek-tuned LLM-driven extractor for headlines and summaries with enforced output schemas, and a sentiment classifier specialised in corporate-disclosure language. Together they produce comparable, ticker-aware analysis at the rate of thousands of events per day.

What it analyses

• SEC EDGAR filings — every public 8-K, 10-K, 10-Q, Form 4, Form 144, DEF 14A, Schedule 13D/A, and related disclosures from U.S.-listed companies. Wiseek AI does not edit the original filing; it reads it, extracts the structured event payload, and links back to the source on sec.gov.
• Licensed financial news — wire-service reporting from Reuters, Dow Jones Newswires, Moneycontrol, and similar providers. Wiseek AI generates its own summary and analysis; the original publisher is always credited.
• Equity-event signals — material executive transitions, M&A announcements, going-concern warnings, restatements, guidance changes, insider transactions, and unusual ownership concentration patterns.

The importance score (1–10)

Every event Wiseek AI processes receives a single number on a 1–10 scale that estimates how market-moving the event is likely to be. The score is produced by Wiseek's scoring model under a fixed rubric, weighting filing type, deal magnitude, parties involved, insider participation, and historical market reaction across thousands of comparable events. Wiseek displays only events scoring 7 or higher in the public feed to keep signal density high.

Sentiment classifier

Each event also receives a sentiment label — positive, negative, or neutral — reflecting the directional tone of the source content for the named ticker. The classifier is calibrated on corporate-disclosure language so it can distinguish, for example, an 8-K announcing a beat-and-raise (positive) from an 8-K disclosing a going-concern doubt (negative) even when both share neutral, lawyerly phrasing. Sentiment is a tone label, not a price forecast.

Key-event extraction

Wiseek AI extracts a structured list of discrete factual claims from each filing or article — the "what actually happened" stripped of narrative. Where possible the events are pulled verbatim from the source so they are auditable. Examples:

• "Director acquired 10,000 shares at $42.10 — total transaction $421,000."
• "Company guided full-year revenue to $1.2B–$1.3B, up from prior $1.1B–$1.2B."
• "CEO Jane Doe to step down effective September 1, 2026; CFO John Smith named interim CEO."

The structured output is what powers the keyword-scanner alerts: subscribers can match key-event patterns instead of free-text headlines, with much lower false-positive rates.

How Wiseek AI evolves

The scoring rubric, extraction schemas, and sentiment classifier are revised periodically as Wiseek learns from filing patterns and user feedback on calibration. There is no per-article human editorial review — the system runs autonomously the moment a filing or news item is ingested. When the rubric or schemas change in a way that materially shifts past scores, Wiseek notes it in the methodology page changelog.

Coverage is uniform: every U.S.-listed ticker that hits EDGAR runs through the same model stack with the same rubric. Wiseek does not operate a separate "premium" pipeline for paying subscribers — paying users receive different access (real-time alerts, advanced filters, scanner) but the same scores as free users.

What Wiseek AI does NOT do

• Not financial advice. Importance scores and sentiment labels are descriptive interpretations of public information. Nothing on Wiseek constitutes a recommendation to buy, sell, or hold any security.
• Not real-time at the millisecond level. Typical latency from EDGAR/wire publication to Wiseek surface is 30–90 seconds. For deterministic millisecond latency, use a direct exchange feed.
• Not a foundation model trained from scratch. Wiseek AI uses base large language models combined with Wiseek's proprietary prompts, scoring rubric, structured-output schemas, and domain calibration. The IP is in the integration layer, not in pre-training.