What Is a News-to-Signal Pipeline?
A news-to-signal pipeline is a structured workflow that converts raw, unfiltered news into actionable market intelligence. Raw news is high-volume and low-signal: thousands of headlines per day, most irrelevant to your positions or workflow. A pipeline applies filtering, classification, and analysis to extract the small percentage of events that actually move markets.
Catalayer is built around this concept. Every component — the real-time news feed, AI Public Brief, Monitor rules, and Full Analysis — is one stage in a pipeline that starts with a global event and ends with a structured output you can act on.
Why Raw News Is Not Enough
If you subscribe to a financial news RSS feed, you get volume. A typical financial publisher produces 200–500 headlines per day. An aggregated feed of 50 sources generates tens of thousands. The problems:
- No relevance scoring: A minor corporate press release sits next to a rate decision that moves markets
- No context: The headline tells you what happened but not why it matters or which assets are affected
- No deduplication: The same story appears 10–20 times across different publishers
- No actionability: Reading raw news does not tell you what to monitor or what to do next
A pipeline solves each of these problems by adding structured stages between raw ingestion and your decision.
Step 1: Collect Market-Moving News
Catalayer ingests over 50 financial news sources — wire services, financial publishers, regulatory feeds, sector-specific outlets, and macroeconomic data releases. All sources are deduplicated and normalized. Stories arrive with sub-60-second latency from publication.
The first stage of the pipeline is simply: get the right news, fast. Catalayer does this by sourcing from direct publisher feeds rather than relying on search-engine crawl, which introduces latency of minutes to hours.
What to set up:- Access the Catalayer News terminal at
/newsfor a live view of all incoming stories - Filter by ticker, sector, or topic to narrow the feed to your coverage universe
Step 2: Identify Entities and Themes
Not all news is created equal. An earnings miss from a $500B company is structurally different from a regulatory comment from a foreign ministry. Catalayer classifies each story by:
- Entities: tickers, companies, central banks, regulators, commodities
- Event type: earnings, M&A, FDA decision, rate decision, geopolitical, macro data release
- Sector: technology, healthcare, energy, financials, macro
- Market impact direction: bullish, bearish, mixed, or neutral
This classification is the second stage of the pipeline. Without it, every story looks identical.
Step 3: Generate a Catalayer AI Public Brief
For every story that passes relevance thresholds, Catalayer generates an AI Public Brief — a structured summary available to all users at no cost. The Public Brief includes:
- A plain-English summary of what happened
- The market impact direction and estimated magnitude
- Key variables affecting the outcome
- Affected sectors and related assets
The Public Brief converts a raw headline into a structured object that describes what the event means for markets.
Example: A Federal Reserve press conference generates a Public Brief that identifies: the hawkish or dovish signal, rate path implication, affected asset classes (bonds, equities, USD), and sector-level impacts such as rate-sensitive utilities and real estate.Step 4: Monitor the Signal
Once you identify a signal worth tracking — a specific ticker, event type, or market theme — you create a Monitor rule in Catalayer. Monitor rules use boolean logic:
NVDA AND earnings— all Nvidia earnings coverage"Fed" AND ("rate cut" OR "rate hike")— Federal Reserve rate decisionsoil AND (OPEC OR sanctions)— energy market catalysts
When a new story matches your rule, Catalayer routes an alert to Telegram, the Island desktop app, or your API webhook — within 60 seconds of publication.
Signal monitoring converts a one-time event into ongoing coverage of a theme you have identified as important.Step 5: Escalate to Full Analysis (Plus)
The AI Public Brief provides the public-tier intelligence. Catalayer Plus subscribers access the Full Analysis layer, which adds:
- Market Prediction: direction and magnitude for specific assets over a 1–5 day horizon
- What to Watch: specific follow-on events that would confirm or contradict the initial signal
- Signal Chain: how this event connects to related macro and sector catalysts
- Monitor-ready context: pre-formatted rule descriptions for immediate monitoring setup
Full Analysis is the deepest stage: it turns a classified event and its public brief into a structured, actionable intelligence package.
Example Workflow: Oil Sanctions News
| Stage | Output |
|---|---|
| Ingest | Raw headline: "US announces additional sanctions on Iranian oil exports" |
| Classify | Entity: Iran, Oil; Event type: geopolitical/sanctions; Sector: energy |
| Public Brief | Summary + impact: bullish crude, bearish European refining margins; key variable: allied enforcement |
| Monitor | Rule fires: oil AND (Iran OR sanctions) |
| Full Analysis (Plus) | WTI +1.5-3.5% short-term; European airline sector pressure; watch for IEA strategic reserve announcement |
Getting Started
- Access the news feed: Visit
/news— no account required for public content - Set up a Monitor rule: Create a free account and configure your first keyword rule at
/monitor - Subscribe for Full Analysis: Upgrade to Catalayer Plus for predictions and signal chains at
/plans - Integrate via API: Use the Catalayer API to consume structured news data in your workflows — see
/integrateand/documentation
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Catalayer AI Public Brief and Full Analysis are generated by the Catalayer AI engine, which processes real-time news against a knowledge base of over 11,000 market patterns, company events, and macro indicators.