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liquidmert

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// repository documentation

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# 📊 Podscan

Podscan is a podcast intelligence platform that continuously scans, transcribes, and indexes podcast conversations at scale. It enables full-text search, real-time alerts, analytics, and programmatic access across millions of podcast episodes.

Website: https://podscan.fm

---

## 🔍 Overview

Podcasts represent one of the largest sources of long-form conversational content on the internet. However, spoken audio has historically been difficult to search, analyze, and monitor in real time.

Podscan treats podcasts as structured data. By converting audio into searchable transcripts and metadata, Podscan enables users to discover trends, track mentions, and extract insights from the global podcast ecosystem.

Common use cases include:
- Brand and keyword monitoring
- Competitive and market research
- Podcast discovery and outreach
- Audience and trend analysis
- Data ingestion for downstream systems

---

## 🏗️ System Architecture

### High-Level Architecture

---

### Data Ingestion Pipeline

```text
+-------------------+
| Podcast Feeds     |
| (RSS / Direct)    |
+---------+---------+
          |
          v
+---------v---------+
| Audio Processing  |
| & Transcription   |
+---------+---------+
          |
          v
+---------v---------+
| Indexing & NLP    |
| • Keywords        |
| • Entities        |
| • Topics          |
+---------+---------+
          |
          v
+---------v---------+
| Search & Alerts   |
+-------------------+
```

---

## ⭐ Core Features

### 🔎 Full-Text Search

Search across millions of podcast episodes using:
- Keywords and phrases
- Podcast or episode metadata
- Language and duration
- Audience size and reach estimates

Search results are indexed at the transcript level for contextual accuracy.

---

### ⏱️ Real-Time Alerts

Users can configure alerts for:
- Brand or keyword mentions
- Topic-specific conversations
- Newly released episodes matching defined criteria

Alerts can be delivered via email or programmatic integrations.

---

### 📊 Analytics & Insights

Podscan provides aggregated insights including:
- Topic and keyword trends over time
- Estimated audience reach
- Competitive presence across podcasts
- Discovery of relevant podcasts and guests

---

### 🧠 API & Developer Access

Podscan offers developer access for programmatic use cases:
- REST API for search and metadata
- Streaming or firehose-style data access
- Transcript and analytics export

Designed for integration with internal tools, dashboards, and data pipelines.

---

## 🧠 Product Principles

- **Audio as data** — spoken content treated as structured information  
- **Search-first** — transcripts indexed for precision and recall  
- **Real-time awareness** — alerts triggered as new content is published  
- **Scalability** — designed to handle millions of episodes  
- **Developer-friendly** — APIs for automation and integration

---

## 🧩 Repository Structure (Example)

```text
.
├── backend/          # Indexing, search, alerts
├── api/              # Public and internal APIs
├── web/              # Web UI
├── ingestion/        # Feed polling and transcription
├── docs/             # Documentation
├── .github/          # CI/CD workflows
└── README.md
```

---

## 🚀 Getting Started

> Adjust this section to match your actual repository setup.

### Requirements

- Node.js >= 18
- npm or yarn
- Access to transcription and storage services

### Setup

```bash
git clone https://github.com/<org>/podscan.git
cd podscan
npm install
```

Create a `.env` file with required configuration.

Run locally:

```bash
npm start
```

---

## 🧪 Testing

```bash
npm test
```

Tests should validate:
- Transcript ingestion
- Search accuracy
- Alert triggering
- API response correctness

---

## 🔐 Security & Privacy

- Data access is permissioned
- Transcripts and analytics are user-scoped
- No unauthorized redistribution of content

Security issues should be reported responsibly.

---

## 📄 License

Specify license here (e.g. MIT, proprietary).

---

## 🏢 Company

Podscan is built to make podcast conversations searchable, measurable, and actionable — enabling better discovery, monitoring, and intelligence across the audio ecosystem.

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