Apify

What is Apify?

Apify is a web data extraction and browser automation platform built around a simple idea: most of the useful information on the internet still lives on websites, not in clean APIs. The company was founded in Prague by Jan Čurn and Jakub Balada after they ran into this problem themselves while aggregating car listings. Instead of building one scraper for one project, they turned the hard parts of scraping into a platform, including cloud execution, proxy management, scheduling, storage, and a marketplace of reusable tools.

Today, Apify is best understood as both infrastructure and a marketplace. Its core unit is the "Actor", a cloud program that can scrape a site, automate browser actions, transform data, or connect web data to another system. Apify says its Store now includes more than 20,000 Actors, created by both the company and outside developers. That matters because many visitors do not start by writing code. They start by asking, "Can I get Google Maps results, LinkedIn data, Instagram posts, ecommerce prices, or search results without building everything myself?" Often, the answer on Apify is yes.

We researched Apify as a tool for developers, operators, founders, and teams building AI systems that need current information from the web. It has grown into one of the most established names in scraping infrastructure, with customers ranging from startups to large companies such as Microsoft, Accenture, Siemens, Intercom, Roche, and T-Mobile. It is especially relevant now because AI agents need fresh data, not just model training data, and Apify has been pushing hard into that role with integrations for agent frameworks and Model Context Protocol support.

Key Features

• Actor Store: Apify’s biggest advantage is scale. The Store lists more than 20,000 Actors for scraping, crawling, automation, and data processing. In practice, this can cut weeks of custom development down to minutes if someone has already built the extractor you need.

• Custom Actor Development: Teams are not limited to the marketplace. Developers can build their own Actors in JavaScript or Python, package them in containers, and run them on Apify’s cloud. This matters when your target site is unusual, your workflow has business-specific logic, or you need control over retries, parsing, and output format.

• Managed Cloud Execution: Apify runs Actors in its own infrastructure, so users do not need to manage servers, cron jobs, Docker hosts, or queue workers. You choose memory and runtime settings, and the platform handles execution. For teams running jobs daily or at large scale, that removes a lot of operational burden.

• Proxy Infrastructure: Apify includes access to datacenter proxies, residential proxies, and specialized Google SERP proxies. This is one of the reasons it works on harder targets where simpler scraping tools fail. Residential proxies cost extra, but for many blocked sites they are the difference between a working workflow and a dead one.

• Crawlee SDK: Apify also maintains Crawlee, its open-source scraping framework. Developers can use it to build crawlers with session handling, retries, concurrency control, and browser automation support. This matters because it gives technical teams a path to start locally, test thoroughly, then deploy to Apify when they are ready.

• Browser Automation: Apify supports headless browser workflows for sites that render content with JavaScript. That means it can interact with modern web apps, not just static HTML pages. If your target requires clicks, scrolling, logins, or client-side rendering, this is often essential.

• Datasets and Key-Value Storage: The platform includes built-in storage for extraction results and run state. Data can be exported as JSON, CSV, XML, Excel, RSS, or HTML. For teams feeding BI tools, spreadsheets, vector databases, or downstream APIs, this removes another integration step.

• Scheduling and Webhooks: Apify can run jobs on schedules with cron expressions and trigger webhooks on events like success or failure. That sounds basic, but it changes the product from a one-off scraper into recurring infrastructure. Many teams use this for daily pricing checks, lead enrichment, and content monitoring.

• API-First Platform: Nearly everything in Apify can be controlled through its API, from running Actors to fetching datasets and managing schedules. Apify reported API calls growing from 3.6 billion to 6.8 billion during 2023 to 2024, with 87% of Actor runs happening through the API. That tells you how people really use it, not as a toy dashboard, but as a backend service inside larger systems.

• AI Agent Integrations: Apify has invested heavily in AI tooling, including MCP support and integrations with frameworks like LangGraph, CrewAI, and Mastra. For teams building agents that need current web data, this is one of the clearest reasons to look at Apify now rather than treating it as "just a scraper."

Use Cases

One of the clearest Apify stories is competitive intelligence. We found user reports describing teams that used Apify to monitor competitor pricing, stock availability, and website changes across dynamic sites that changed layout often. One reviewer said Apify reduced their data collection time by more than 70% because they no longer had to track competitor data manually. That is the kind of use case where the platform’s scheduling, proxies, and browser automation all work together. The value is not in one scrape, it is in having an always-on pipeline that keeps producing current data.

Another strong use case is lead generation and sales research. Companies use Apify Actors to gather company details, directory listings, contact information, and business metadata from public web sources. In practice, this is less about "scraping for scraping’s sake" and more about building a repeatable prospecting engine. A founder or sales ops team can run jobs on a schedule, export structured data, and feed a CRM or outbound system with fresh targets.

Apify is also being used as infrastructure for AI systems. The company has leaned into this hard, and the fit is real. Teams building RAG systems use Apify to scrape websites, help centers, product pages, and news sources, then push that data into vector stores or knowledge pipelines so their assistants answer with current information rather than stale training data. The same pattern shows up in AI agents that need to research competitors, gather market data, or check live facts on the web before taking action.

At the enterprise end, Apify’s customer list tells part of the story. Microsoft, Accenture, Siemens, Roche, Intercom, and T-Mobile are all cited as customers. The interesting part is not just the logos. It is what those logos imply. Large teams usually do not adopt scraping tools because they are fun. They adopt them because they need repeatable web data collection with governance, APIs, and enough reliability to plug into business processes. Apify’s growth to roughly $25 million in ARR also suggests it is not surviving on hobby users alone.

Strengths and Weaknesses

Strengths:

Apify is unusually strong when the target site is difficult. Reviews repeatedly point to its handling of browser fingerprinting, session rotation, and proxy management. In plain terms, users often come to Apify after simpler no-code tools break on dynamic or protected sites. One reviewer described the difference clearly: instead of spending weeks writing and maintaining custom scrapers, they could deploy a pre-built Actor in minutes and rely on Apify’s infrastructure to handle the ugly parts.

Its marketplace is a real moat. Many competitors are easier for a first scrape, but they do not have anything close to 20,000 reusable tools. That changes the buying decision. If your use case matches an existing Actor, Apify can feel dramatically faster than building from scratch. For developers, the Store also acts like a library of patterns. You are not just buying a run button, you are buying accumulated knowledge about how to extract data from specific sites.

Apify also is known for technical depth. Teams that need APIs, schedules, webhooks, custom code, storage, and integrations can keep growing inside the same platform rather than switching tools after the prototype stage. This is where it compares well against easier products like Browse AI or Thunderbit. Those tools may get a non-technical user to a first result faster, but Apify tends to hold up better once the workflow becomes part of production infrastructure.

Its AI positioning is stronger than many older scraping platforms. Support for MCP and agent frameworks means Apify is not waiting around to see if agents matter. It is actively trying to become the web data layer for them. For our visitors building agent products, this is one of the biggest reasons Apify feels current rather than legacy.

Weaknesses:

The learning curve is real. Apify can be friendly when a pre-built Actor fits your needs exactly, but once it does not, the experience changes fast. Reviews and comparisons consistently note that non-technical users hit a wall when they need custom logic, debugging, or changes to extraction behavior. Compared with Browse AI or Thunderbit, Apify asks more from the user.

Pricing can also be harder to predict than flat-rate tools. Apify charges based on compute usage, and proxy costs can stack on top, especially with residential IPs. That is fair for infrastructure, but it means teams need to benchmark real jobs before they know what they will spend. A simple scrape might cost pennies. A browser-heavy workflow across many pages can become meaningfully expensive.

There is also the ongoing maintenance reality that comes with scraping. Even with Apify’s infrastructure, websites still change. Layouts break. Anti-bot measures evolve. If you depend on a specific Actor for a business-critical workflow, someone still needs to watch it. Apify reduces the infrastructure burden, but it does not remove the underlying fragility of web extraction itself.

Finally, it is not always the best choice for very simple jobs. If someone just wants to grab a small table from a website once a month, Apify can feel like a lot of machine for a small task. Some alternatives are less powerful, but easier to pick up in five minutes.

Pricing

• Free: $0/month Includes $5 of monthly usage with no credit card required. This is enough for testing, small experiments, and getting a feel for how Actors, datasets, and the console work.

• Starter: usage billed at about $0.30 per compute unit This is the first paid tier for individuals and small teams. It works for light recurring jobs, but compute-heavy browser runs and proxy usage can push costs up quickly.

• Scale: usage billed at about $0.25 per compute unit This tier lowers the unit cost and is where regular business usage starts to make more sense. Apify also offers startup and academic discounts, which can materially change the math for early-stage teams.

• Growth: custom higher-volume tier Designed for larger usage with better economics and more support. At this point, teams are usually running production pipelines, not experiments.

• Enterprise: custom pricing Includes negotiated pricing, support commitments, and enterprise features. This is the route for large organizations with high-volume scraping, internal platform teams, or strict support requirements.

What users actually spend depends less on the plan name and more on the job shape. Browser automation, retries, residential proxies, and large data volumes all increase cost. That means Apify can be very cheap for API-like extraction from stable sites, and much more expensive for dynamic, protected targets. Compared with flat monthly tools, Apify is often better value at scale, but less predictable on day one. The hidden gotcha is usually proxies, especially residential ones.

Alternatives

Browse AI

Browse AI is one of the clearest alternatives for non-technical users. It focuses on visual setup and faster first success, so someone can point at a page, teach the tool what to extract, and get results without understanding Actors, containers, or proxy strategy. We would point visitors toward Browse AI if they want the easiest path to a small workflow. We would point them back to Apify if the site is difficult, the workflow needs to scale, or they expect to build this into a real product.

Thunderbit

Thunderbit also competes on simplicity. Its pitch is basically that many scraping jobs should feel like spreadsheet work, not infrastructure work. That is attractive for solo operators and business users who just want data out. Compared with Apify, it tends to be easier to approach, but it does not offer the same marketplace depth or technical range. If your team is moving toward recurring, production-grade extraction, Apify usually has more room to grow.

Octoparse

Octoparse has been around for a long time and is still a common choice for business users who want visual scraping software. It is a familiar option for point-and-click extraction and can be a good fit for simple websites. The tradeoff is that Apify is much stronger as cloud infrastructure and developer tooling. Octoparse feels more like scraping software. Apify feels more like a platform.

n8n

n8n is not a direct scraper competitor so much as an automation platform that can sit around scraping tools. Teams that already live in n8n may prefer to orchestrate workflows there and call Apify when they need serious web extraction. If your main problem is connecting many SaaS tools together, n8n may be the better center of gravity. If your main problem is getting web data reliably, Apify is the stronger specialist.

Gumloop

Gumloop is interesting for teams that want AI workflows and scraping in one place. It leans more toward AI automation than pure extraction infrastructure. Some builders may prefer that all-in-one direction, especially in early prototypes. Apify still looks stronger when the web data side becomes hard, high-volume, or central to the product.

FAQ

What is Apify used for?

Apify is mainly used for web scraping, browser automation, and recurring data collection. Teams use it for competitor monitoring, lead generation, market research, AI data pipelines, and website automation.

Is Apify a no-code tool?

Partly. You can run many pre-built Actors without writing code, but custom workflows often need JavaScript or Python. It is more accurate to call it low-code to developer-friendly rather than fully no-code.

How do I get started?

Start with the free plan, browse the Actor Store, and run a pre-built Actor against a small use case. If that works, you can add schedules, exports, API calls, or custom code later.

How long to set up?

If an existing Actor matches your need, setup can take a few minutes. If you need custom extraction logic or have a difficult target site, setup can take hours or days depending on complexity.

Do I need to know how to code?

Not always. Many users get value from pre-built Actors and the console interface. But if your workflow needs customization, debugging, or production hardening, coding skills help a lot.

What are Actors in Apify?

Actors are small cloud programs that do a job, such as scraping a site, automating a browser, or transforming data. They are the basic building blocks of the platform.

Can Apify handle JavaScript-heavy websites?

Yes. This is one of its strengths. Apify supports browser automation for sites that load content dynamically, require scrolling, or depend on client-side rendering.

Does Apify include proxies?

Yes, but proxy usage is not always included in the base compute cost. Datacenter, residential, and SERP proxies have different pricing, and residential proxies are often the expensive part.

Is Apify good for AI agents?

Yes. Apify has become one of the more relevant tools in this category because it offers MCP support and integrations with agent frameworks like LangGraph and CrewAI. It is a practical way to give agents live web access.

Is Apify better than Browse AI?

It depends on what you need. Browse AI is usually easier for non-technical users and quick one-off tasks. Apify is stronger for harder sites, larger workflows, APIs, custom code, and production use.

Can I export data to CSV or JSON?

Yes. Apify supports exports in JSON, CSV, XML, Excel, RSS, and HTML. That makes it easy to move data into spreadsheets, BI tools, databases, or downstream apps.

What are the biggest downsides?

The main downsides are learning curve, cost predictability, and maintenance when websites change. Apify handles a lot for you, but scraping still has moving parts, and those moving parts do not disappear just because the platform is good.