🌐 RSS Aggregator: AI-Powered RSS Aggregator & Summarizer

Enterprise-grade RSS aggregator with AI-powered summarization. Collects, filters, and processes feeds from any source. Ideal for content analysis, news monitoring, and AI training. Features keyword filtering, metadata extraction, and structured output in JSON/CSV. Built with Hugging Face for advanced summaries.

High-quality RSS Feed Aggregator & Processor for Content Teams, Researchers, and AI Engineers

Automatically aggregates RSS feeds, filters by keywords, extracts summaries, and optionally generates AI-powered summaries — clean, structured, ready for analysis or AI.

Built for:

• Content aggregators & news monitoring teams
• Researchers tracking academic papers and publications
• AI/ML engineers building content datasets
• Marketing teams monitoring industry trends
• Data analysts processing feed data

✅ Smart keyword filtering
✅ AI-powered summarization (Hugging Face transformers)
✅ Multiple feed support (1-5 feeds recommended)
✅ Rich metadata extraction (date, author, tags, description)
✅ Rate limiting & respectful crawling
✅ AI-ready structured output

👉 Runs on Apify • No code required

🚀 Why This Aggregator

✔ Purpose-Built for RSS Processing
Intelligently aggregates and processes RSS feeds from any source — news sites, academic journals, blogs, corporate feeds.

✔ AI Summarization Ready
Optional integration with Hugging Face transformers (BART, Pegasus) for advanced AI-powered summarization of feed entries.

✔ Clean & Structured Output
Extracts only meaningful content — title, link, summary, author, tags, publication date — ready for analysis.

✔ Smart Keyword Filtering
Filter entries by custom keywords (case-insensitive) across title, summary, and tags for relevance.

✔ AI & ML Ready
Structured JSON/CSV output perfect for RAG systems, LLM fine-tuning, or training datasets.

✔ Fast & Efficient
Powered by feedparser — excellent for RSS/Atom feeds. Lightweight and fast processing.

✔ Safe & Controlled Processing
Configurable rate limiting, entry limits per feed, and graceful error handling.

💼 Use Cases

• News monitoring — Track industry news and trends from multiple sources
• Academic research — Aggregate papers from arXiv, PubMed, and other academic feeds
• Content curation — Collect and filter relevant content for newsletters or blogs
• AI training data — Generate clean datasets for LLM fine-tuning or RAG systems
• Competitive intelligence — Monitor competitor blogs and news feeds
• Market research — Track product announcements and industry updates

📊 Supported Sources

• News feeds — TechCrunch, Reuters, BBC, Guardian, etc.
• Academic feeds — arXiv, PubMed, academic journals
• Blog feeds — Medium, WordPress, custom blog RSS
• Corporate feeds — Company blogs, press releases, announcements
• Any RSS/Atom feed — Standard-compliant feeds

⚙️ How It Works

1. Provide RSS feed URLs (1-5 feeds recommended)
2. Set custom keywords and processing options
3. Optionally enable AI summarization
4. Run the Actor
5. Download clean, structured RSS datasets

🧩 Input Configuration

Example JSON Input

{
  "rssFeeds": [
    "https://arxiv.org/rss/cs.AI",
    "https://techcrunch.com/feed/"
  ],
  "maxEntriesPerFeed": 10,
  "keywords": [
    "AI",
    "machine learning",
    "artificial intelligence"
  ],
  "enableSummarization": true,
  "enableAISummarization": true,
  "aiModelName": "facebook/bart-large-cnn",
  "aiMaxLength": 1024,
  "aiMinLength": 50,
  "aiMaxSummaryLength": 150,
  "delayBetweenFeeds": 1.0
}

Key Options

• rssFeeds — List of RSS feed URLs to aggregate (required, 1-5 recommended)
• maxEntriesPerFeed — Maximum entries per feed (0 = unlimited, default: 10)
• keywords — Custom keywords for filtering entries (case-insensitive, empty = all entries)
• enableSummarization — Extract summary/description from feeds (default: true)
• enableAISummarization — Use Hugging Face AI for advanced summarization (default: false)
• aiModelName — Hugging Face model identifier (default: "facebook/bart-large-cnn")
• aiMaxLength — Maximum input length for AI model (default: 1024 tokens)
• aiMinLength — Minimum summary length (default: 50 tokens)
• aiMaxSummaryLength — Maximum summary length (default: 150 tokens)
• delayBetweenFeeds — Delay in seconds between feeds for rate limiting (default: 1.0)

📂 Output Dataset

All entries are stored in the default Apify dataset with the following structure:

Example Output Record

{
  "title": "Adobe hit with proposed class-action, accused of misusing authors' work in AI training",
  "link": "https://techcrunch.com/2025/12/17/adobe-hit-with-proposed-class-action-accused-of-misusing-authors-work-in-ai-training/",
  "published": "2025-12-18T00:44:55",
  "summary": "The lawsuit is just the latest in a string of copyright-related legal complaints aimed at the AI industry.",
  "feedTitle": "TechCrunch",
  "feedUrl": "https://techcrunch.com/feed/",
  "author": "Lucas Ropek",
  "tags": [
    "AI",
    "Adobe",
    "Anthropic",
    "artificial intelligence"
  ]
}

With AI Summarization

When enableAISummarization: true, the summary field contains AI-generated summaries:

{
  "title": "Breakthrough in Quantum Computing",
  "link": "https://example.com/quantum-breakthrough",
  "published": "2025-12-15T10:30:00",
  "summary": "Researchers achieve significant milestone in quantum error correction, bringing practical quantum computing closer to reality. The new method reduces error rates by 50%...",
  "feedTitle": "Science News",
  "feedUrl": "https://example.com/feed.xml",
  "author": "Dr. Jane Smith",
  "tags": ["quantum computing", "research", "technology"]
}

🤖 AI Summarization Models

Supported Hugging Face models for summarization:

• facebook/bart-large-cnn (default) — Best for news articles and general content
• google/pegasus-xsum — Optimized for news summaries
• Any summarization model — Compatible with Hugging Face transformers

The Actor automatically falls back to basic extraction if AI summarization fails or is unavailable.

🏁 Getting Started

Quick Start on Apify

1. Click "Try for free" on Apify
2. Paste RSS feed URLs (e.g., https://techcrunch.com/feed/)
3. Customize keywords and options
4. Optionally enable AI summarization
5. Run and download your dataset

📈 Performance

• Processing Speed — ~1-2 seconds per feed (depending on entries)
• Rate Limiting — Configurable delay between feeds (default: 1s)
• Memory Efficient — Processes feeds sequentially
• Scalability — Handles 1-5 feeds optimally (can process more)

🔧 Advanced Configuration

Custom AI Models

You can use any Hugging Face summarization model:

{
  "enableAISummarization": true,
  "aiModelName": "google/pegasus-xsum",
  "aiMaxLength": 2048,
  "aiMinLength": 100,
  "aiMaxSummaryLength": 200
}

📧 Support

• Email: kidaxxb@gmail.com
• Response within 24 hours
• Issues: Use Apify Issues tab

Tags: RSS, feed aggregator, content processing, AI summarization, Hugging Face, news aggregation, feed parser, content analysis, RAG, LLM training, data extraction

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