The Best Apify Actors for AI and LLM Projects in 2025

The Apify marketplace has over 3,500 actors. Most were built for data extraction use cases that predate the LLM era — structured tables, CSV exports, database-ready schemas. A growing subset are built specifically for AI pipelines: RAG context, training data, agent tools, and real-time grounding data.

TL;DR: The best Apify actors for AI/LLM work prioritize clean output format (markdown, not raw HTML), per-result billing (you pay only for successful data), and maintenance recency (updated within 6 months). Top picks: RAG Crawler for knowledge base indexing, Reddit Scraper for training data and brand monitoring, Google Trends Pro for grounding data, ATS Jobs for skills demand tracking.

This is a curated list of actors worth knowing for AI/LLM use cases in 2025, with honest notes on where each one excels and where it falls short.

Criteria

For this list, we evaluated actors on:

• Output format: Does it produce markdown, clean text, or LLM-ready JSON? Or does it dump raw HTML you have to clean yourself?
• Reliability: What is the actual success rate in production? Actor pages show ratings but not failure rates.
• Billing fairness: Does it charge per result or per run? Per-result billing (PPE) means you pay only for data you receive.
• Maintenance: When was it last updated? Anti-bot landscapes change monthly.

Content and Web Crawling

RAG Crawler (themineworks/rag-crawler)

Built specifically for RAG pipelines. Outputs pre-chunked markdown with token counts. Uses Playwright for JavaScript-rendered content. Content extraction removes navigation, headers, and boilerplate. PPE billing — pay per page.

Best for: Indexing documentation sites, product pages, or knowledge bases into a vector store. Avoid if: You need raw HTML output for custom processing.

Website Content Crawler (apify/website-content-crawler)

The most popular general-purpose web crawler on Apify. High quality output, well-maintained, large install base means bugs get reported and fixed quickly.

Best for: Large-scale crawls with custom routing logic. Highly configurable. Avoid if: You want a simple fire-and-forget setup — the configurability can be overwhelming.

Social Media Data

Reddit Scraper (themineworks/reddit-scraper)

Uses Reddit’s OAuth with a public Android client ID — no developer account required. Full nested comment trees, deep historical backfill, PPE billing per post scraped.

Best for: Brand monitoring, sentiment training data, subreddit analysis, LLM fine-tuning datasets. Reliability: High — the OAuth approach is more stable than session-based scrapers.

Threads Scraper (themineworks/threads-scraper)

Handles Threads’ Instagram-backed authentication. Profile posts, reply threads, engagement metrics.

Best for: Social listening on Threads, competitive brand monitoring, influencer research.

Twitter / X Scraper (various actors)

Multiple actors available; quality varies significantly. Apify’s own apify/twitter-scraper is the most maintained. Note that Twitter’s API now costs $100/month minimum, making scrapers the practical choice for most budgets.

Best for: Trend monitoring, competitor analysis, real-time event tracking. Note: Twitter actively blocks scrapers. Expect higher failure rates than Reddit or Threads.

Job Market Data

ATS Jobs (themineworks/ats-jobs)

Aggregates public job board APIs from Greenhouse, Lever, and Ashby. Zero authentication required. Normalized output schema across all three platforms.

Best for: Recruiting automation, labor market intelligence, skills demand tracking. Limitation: Only covers companies using these three ATSes — excludes companies using Workday, iCIMS, or custom boards.

Naukri Jobs (themineworks/naukri-jobs)

India-specific job data with session warming to bypass Akamai bot detection. Salary data, experience ranges, work mode (WFH/hybrid/office).

Best for: Indian market recruitment tools, salary benchmarking, India tech talent intelligence.

LinkedIn Jobs (various actors)

Multiple actors attempt LinkedIn scraping with varying success. LinkedIn actively blocks most scraping attempts. Expect 60-80% success rates on a good day.

Best for: Companies that specifically need LinkedIn’s unique job data (LinkedIn Easy Apply tracking, employee counts). Alternative: Use ATS Jobs for the same companies — it is more reliable and the data is equivalent.

Search and Trends

Google Trends Pro (themineworks/google-trends-pro)

Returns interest over time, interest by region, related queries, and related topics. No browser needed — uses the explore API to get widget tokens, then residential proxies for widgetdata.

Best for: Keyword research, product validation, seasonal demand forecasting, competitive intelligence.

Google Search Results Scraper (apify/google-search-scraper)

Extracts organic results, featured snippets, and People Also Ask boxes from Google Search. Uses Apify’s GOOGLE_SERP proxy pool (paid plan required for reliable access).

Best for: SERP monitoring, competitor SEO tracking, content research. Note: Requires the Apify Scale plan ($99/month) for the GOOGLE_SERP proxy access needed for reliable operation.

E-commerce Data

Amazon Product Scraper (apify/amazon-product-scraper)

Extracts product details, prices, and reviews. Amazon’s login requirement for reviews caused widespread breakage in late 2024; check the current build status before relying on it.

Best for: Price monitoring, product research, review sentiment analysis.

AI-Specific Use Case Matrix

Use case	Recommended Actor(s)
RAG knowledge base	RAG Crawler
LLM fine-tuning dataset	Reddit Scraper, Website Content Crawler
Agent grounding data	Google Trends Pro, ATS Jobs
Brand monitoring	Reddit Scraper, Threads Scraper
Competitive intelligence	Google Trends Pro, LinkedIn Jobs
Salary intelligence (India)	Naukri Jobs
Skills demand analysis	ATS Jobs, Naukri Jobs

What to Check Before Committing to an Actor

1. Last updated date: If the actor was last updated more than 6 months ago and targets a site with bot protection, assume it is broken or degraded.
2. Issue count: Active issues on the actor page signal known problems.
3. PPE vs per-run billing: Per-run actors charge you even on empty runs. PPE actors only charge on successful results.
4. Example output: Download the sample dataset and check if the schema matches what you need before running at scale.

Frequently Asked Questions

What criteria distinguish a good Apify actor for AI use cases from a generic scraping actor?

Three criteria matter most: output format (clean markdown or structured JSON, not raw HTML that requires your own parsing), billing model (pay-per-result so you don’t pay for failed or empty runs), and maintenance recency (updated within 6 months means the author is actively maintaining compatibility with the target site). Actors that return raw HTML force you to write fragile parsing logic that breaks every time the site redesigns.

Why does per-result billing (PPE) matter when selecting actors for AI pipelines?

PPE means you pay only for successfully scraped items. Per-run billing charges you even when the actor returns zero results — which happens regularly when sites block scrapers, rate-limit requests, or return error pages. For AI pipelines where you’re processing results downstream, paying for empty runs wastes both money and pipeline compute. At scale, the difference between PPE and per-run billing can be 2-5x total cost.

What is the best Apify actor for building a RAG knowledge base?

The RAG Crawler is purpose-built for this: it handles JavaScript rendering, respects crawl depth limits, and returns pre-chunked Markdown rather than raw HTML. Pre-chunking is the key advantage — it saves you from writing your own chunking logic and produces semantically coherent chunks aligned to document structure. For 100 pages, the total cost including embedding is under $1.

How do you evaluate whether an Apify actor is still maintained and reliable?

Check four signals: (1) last updated date in the Apify store — anything over 6 months on a site with active bot protection is likely degraded; (2) open issues count — active issues signal known problems; (3) billing model — PPE actors have stronger incentive for the author to maintain quality since they only earn on successful results; (4) example dataset — download the sample and verify the schema matches what you actually need before committing to a large run.

Which Apify actors are best suited for LLM fine-tuning dataset creation?

Reddit Scraper is the strongest for instruction fine-tuning — it collects threaded Q&A pairs with community vote scores that function as quality labels. RAG Crawler is best for domain knowledge datasets — crawl any authoritative site and get chunked markdown ready for embedding or training. Google Trends Pro provides grounding data for temporal and geographic context. Combine Reddit Scraper for conversational pairs with RAG Crawler for factual content to cover both instruction-following and knowledge dimensions.