# 🚀 AI Product Launch Intelligence Agent

### 🎓 FREE Step-by-Step Tutorial 
**👉 [Click here to follow our complete step-by-step tutorial](https://www.theunwindai.com/p/build-a-multi-agent-product-launch-intelligence-app) and learn how to build this from scratch with detailed code walkthroughs, explanations, and best practices.**

A **streamlined intelligence hub** for Go-To-Market (GTM) & Product-Marketing teams.  
Built with **Streamlit + Agno (GPT-4o) + Firecrawl**, the app turns scattered public-web data into concise, actionable launch insights.

## 3 Specialized Agents in Coordinated Team

| Tab | What You Get |
|-----|--------------|
| **Competitor Analysis Agent** | Evidence-backed breakdown of a rival's latest launches – positioning, differentiators, pricing cues & channel mix |
| **Market Sentiment Agent** | Consolidated social chatter & review themes split by 🚀 *positive* / ⚠️ *negative* drivers |
| **Launch Metrics Agent** | Publicly available KPIs – adoption numbers, press coverage, qualitative "buzz" signals |

Additional goodies:

* 🔑 **Sidebar key input** – enter OpenAI & Firecrawl keys securely (type="password")
* 🧠 **Coordinated multi-agent team** – three expert agents work together for richer insight
  * 🔍 Product Launch Analyst (GTM strategist)
  * 💬 Market Sentiment Specialist (consumer-perception guru)
  * 📈 Launch Metrics Specialist (performance analyst)
* ⚡ **Quick actions** – press **J/K/L** to trigger the three analyses without touching the UI
* 📑 **Auto-formatted Markdown reports** – bullet summary first, then expanded deep-dive
* 🛠️ **Sources section** – every report ends with the URLs that were crawled or searched

## 🛠️ Tech Stack

| Layer | Details |
|-------|---------|
| Data | **Firecrawl** async search + crawl API |
| Agents | **Agno Team** (GPT-4o) with FirecrawlTools |
| UI | **Streamlit** wide-layout, tabbed workflow |
| LLM | **OpenAI GPT-4o** |

## 🚀 Quick Start

1. **Clone** the repository

```bash
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd advanced_ai_agents/multi_agent_apps/product_launch_intelligence_agent
```

2. **Install** dependencies

```bash
pip install -r requirements.txt
```

3. **Provide API keys** (choose either option)

   • **Environment variables** – create a `.env` file:
   ```ini
   OPENAI_API_KEY=sk-************************
   FIRECRAWL_API_KEY=fc-************************
   ```
   • **In-app sidebar** – paste the keys into the secure text inputs

4. **Run the app**

```bash
streamlit run product_launch_intelligence_agent.py
```

5. **Browse** to <http://localhost:8501> – you should see three analysis tabs.

## 🕹️ Using the Application

1. Enter **API keys** in the sidebar (or ensure they are in your environment).
2. Type a **company / product / hashtag** in the main input box.
3. Pick a tab and hit the corresponding **Analyze** button – a spinner will appear while the coordinated team works.
4. Review the two-part analysis:
   * Bullet list of key findings
   * Expanded, richly-formatted report (tables, call-outs, recommendations)

## 🤖 How the Coordinated Team Works

The application uses a **coordinated team approach** where three specialized agents work together:

- **Product Launch Analyst**: Evaluates competitive positioning, launch strategies, strengths, and weaknesses
- **Market Sentiment Specialist**: Analyzes social media sentiment, customer feedback, and brand perception  
- **Launch Metrics Specialist**: Tracks KPIs, adoption rates, press coverage, and performance indicators

The team coordinates based on the analysis type requested, ensuring the most appropriate agent handles each task while maintaining consistency and comprehensive coverage across all analysis types.
