FinSage

This template provides an AI-powered investment analysis for any company based on the latest news headlines. It accepts a company name or ticker, fetches recent news, and returns a structured JSON report with sentiment scores, market trends, investment recommendations, and risk notes.

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Link to template

https://templates.buildship.com/template/aAJquzw9-CAq/

By Sanskar's Workspace

Inputs

company

Google

This is a static example using sample inputs. Remix the template to run it with your own values.

Output

Read me

AI-Based Stock Sentiment & Investment Scoring Workflow

📈 AI-Powered Stock Sentiment & Investment Score Generator

This project leverages Buildship's no-code automation platform and OpenAI's language models to create a smart financial analysis tool. By processing real-time news headlines for any public company, the workflow evaluates media sentiment, flags risk signals, and generates an investment recommendation — all within a structured API workflow.

🔍 Overview

This workflow:

Accepts a company name (e.g., "Google", "Tesla")
Fetches the latest news headlines using the NewsAPI
Sends those headlines to an LLM (OpenAI) for analysis
Returns a structured JSON response with:
- Sentiment analysis
- Investment recommendation
- Risk factors
- Confidence score
- Final investment score for ranking

🧠 Key Features

📰 News IntegrationUses NewsAPI to fetch real-time headlines

🧠 AI Sentiment AnalysisOpenAI interprets tone, trends, risks, and investor sentiment

📊 Investment ScoringCalculates a 0–100 score to rank companies based on outlook

⚠️ Caution DetectionFlags layoffs, lawsuits, or product issues from headlines

🔁 REST API InterfaceTriggered via POST with a company name as input

🧱 No frontend includedDesigned solely as a self-contained, API-based backend workflow

🏗️ Workflow Structure

Input Node: Accepts JSON: { "company": "CompanyName" }

NewsAPI Node: - Endpoint: /v2/everything - Params: q={{inputs.company}}, from=2025-06-01, sortBy=popularity, language=en

OpenAI Node (Text Generation): - Prompt: Analyzes sentiment, risk, and price direction - Produces JSON fields: - sentiment_score - sentiment_classification - recommendation - confidence - caution_notes - final_score - etc.

Code Node (Scoring Logic): - Parses OpenAI response - Applies formula: final_score = (sentiment_score * 0.5) + (recommendation_weight * 25) + (confidence * 0.2) - penalty

📥 API Usage

🔗 Endpoint (example)

POST https://api.buildship.com/flow/<your-flow-id>

📨 Request Body

jsonCopy code{ "company": "Tesla" }

📤 Response

{ "company": "Tesla", "sentiment_score": 78, "recommendation": "Hold", "confidence": 85, "caution_notes": "Layoffs in key teams.", "final_score": 82, "price_direction": "→", "top_headlines": [ { "title": "...", "sentiment": "Positive" }, { "title": "...", "sentiment": "Negative" }, ... ] }

📊 Scoring Formula

The investment scoring logic works as follows:

final_score = (sentiment_score * 0.5) + (recommendation_weight * 25) + (confidence * 0.2) - caution_penalty MetricWeight/ImpactSentiment Score0–100 → 50% of total scoreRecommendationBuy=3, Hold=2, Sell=1ConfidenceWeighted at 20%Caution Penalty-15 if risk factors present

🔒 API Keys Used

NewsAPI Key – securely stored in Buildship secrets
OpenAI API – managed by Buildship under LLM tools

📌 Assumptions & Notes

No backend/frontend system required — submission is only the Buildship workflow
Works best when major news stories are available for the target company
Handles one company per request; multiple can be handled with looping extensions

✅ Submission Summary

💡 Project: AI-Powered Stock Investment Analysis API
📦 Platform: Buildship
🧠 AI Engine: OpenAI GPT-4
🔁 Output: JSON structure containing investment insights and final score
📤 Delivery: Hosted API endpoint ready for external use