Get a full stock trade analysis combining price data, news, and AI

Ask about a stock and get back a full trade recommendation built from price trends, news sentiment, and live market context.

How the work actually flows

It branches. Every path runs; all paths must finish before it continues.

Pattern: Parallel Split (2) ยท Synchronisation (3)

flowchart TD trig(("user asks about stock")):::human s0["check price trends"]:::svc s1["combine all signals"]:::task s2["produce trade recommendation"]:::task trig --> s0 s1 --> s2 gx{"+ gather market signals"}:::gate s0 --> gx p00["score news sentiment"]:::task gx -->|"news sentiment"| p00 p10["check breaking catalysts"]:::task gx -->|"market catalysts"| p10 jn{"+ combine signals"}:::gate p00 --> jn p10 --> jn jn --> s1 out[/"full trade recommendation"/]:::out pay{{"data backed decisions faster"}}:::pay s2 --> out out --> pay classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
A stepAn outside serviceA personEvery pathWaits for allResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
AI Agents & Autonomous SystemsAI Chatbots & AssistantsResearch & Market Intelligence
Connects
OpenAITwelveDataNewsAPIPerplexityChart-Img

The problem it solves

Deciding whether to buy, sell, or hold a stock means checking charts, reading news, and watching for breaking catalysts, and doing that thoroughly for one stock can eat up your evening. Most people end up skipping steps and trading on a hunch.

Who it fits

Active individual investors who want a consistent, data-backed process for evaluating a trade before they act.

How it works

  1. You ask about a stock in a chat
  2. Price trends and moving averages are pulled for multiple timeframes
  3. Recent news is scored for sentiment and checked for sell pressure
  4. Live market context is checked for breaking catalysts like earnings or Fed news
  5. AI combines everything into a buy, sell, or hold call with an entry price, stop loss, and target
What you get

Trade decisions grounded in current market data

You get a full trade recommendation for any stock, complete with entry price, stop loss, and target, built from live data.

What you get

A trade recommendation with a confidence score, entry zone, stop loss, profit target, and a chart for reference.

What you need

API access for TwelveData, NewsAPI, Perplexity, and Chart-Img, plus an OpenAI API key.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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