AlphaAI turns the messy, unstructured world of financial news and regulatory filings into clean, machine-readable signals that AI agents and trading bots can act on immediately. Instead of forcing developers to scrape headlines, parse SEC filings by hand, or babysit fragile RSS pipelines, AlphaAI ingests GDELT global event data, publisher RSS feeds, and SEC EDGAR filings, then normalizes all of it into a single structured feed built specifically for automated consumption.
At the core of the product is per-ticker impact analysis. Every news item and filing is mapped to the relevant ticker symbols, tagged with categories, and scored for relevance so that downstream systems can filter out noise and focus only on the events that actually matter to a given position or watchlist. This means a trading bot no longer needs its own NLP stack just to figure out whether a headline about "Acme Corp" is about the company it holds shares in, or whether the story is even market-moving.
A standout feature is AlphaAI's handling of SEC insider transactions. Form 4 filings, which disclose trades by corporate insiders, are parsed and delivered as structured events roughly six minutes after they are published to EDGAR, giving subscribers a meaningful speed advantage over anyone relying on manual review or generic filing trackers. Alongside Form 4 data, AlphaAI also surfaces 8-K material event disclosures and 6-K reports from foreign private issuers, covering a wide swath of the disclosures that move markets.
Integration is built for modern AI and automation workflows. Developers can consume everything through a REST API described by a full OpenAPI 3.1 specification, making it trivial to generate typed clients or plug the feed into existing pipelines. For teams building on top of large language models and autonomous agents, AlphaAI also exposes an OAuth 2.1 secured MCP server, allowing agents to query financial news and filings directly as part of their reasoning loop without custom glue code.
Key features:
- Structured signals derived from GDELT, publisher RSS, and SEC EDGAR
- Per-ticker impact analysis with categories and relevance scoring
- Parsed insider transaction data from Form 4 filings, delivered around six minutes after EDGAR publication
- Coverage of 8-K and 6-K material event disclosures
- REST API documented with an OpenAPI 3.1 specification
- OAuth 2.1 secured MCP server for direct agent integration
Use cases include algorithmic trading systems that need low-latency insider trading alerts, AI research agents that need clean financial context without manual scraping, fintech products that want to enrich their own feeds with structured filing data, and quantitative researchers backtesting event-driven strategies against historical filings and news.
AlphaAI is priced to be accessible for individual developers and small teams. A free tier offers 20 requests per minute and 100 requests per day, enough to prototype an integration or run a small bot. Paid plans start at just $2.99 per month for teams that need higher throughput.
In short, AlphaAI removes the tedious data engineering work of turning financial news and SEC filings into usable signals, letting developers, quants, and AI agents spend their time on strategy and analysis instead of parsing and normalization.
