Forloop
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About
Forloop is a specialized no-code platform built specifically for data professionals who need to gather, clean, and automate data from external sources. It bridges the gap between manual scraping and complex coding by offering a "vibe" no-code interface while remaining Python-first under the hood. The platform allows users to build production-ready pipelines that can track market changes, support pricing strategies, and integrate with existing systems without the typical overhead of traditional data engineering. By empowering data consumers to be independent of data engineers, the tool aims to save organizations significant operational costs while increasing the speed of insight generation. Currently operating as a desktop application for Windows and Mac, the tool enables users to download data directly from browsers and perform automatic data cleaning with minimal manual intervention. Users can build concurrent pipelines, manage large volumes of API requests, and collaborate with team members in shared workspaces. Its workflow is designed to take users from zero to production in just three steps, focusing on high-speed prototyping that can scale into cloud-ready pipelines. It specifically addresses the limitation of internal data by providing the infrastructure to tap into the 99.99% of relevant market data that exists outside a company’s own database. The platform is ideally suited for data analysts, data engineers, and developers working in data-heavy sectors like FMCG, Real Estate, and Logistics. For example, real estate teams use it to connect multiple property websites to their internal systems to automate routine listing updates, while data scientists use it to prepare datasets for AI models significantly faster than traditional manual methods. It is also a valuable resource for growth hackers and RPA developers who need to automate routine data-gathering and cleaning processes without a huge budget or a massive engineering team, allowing for faster adaptation to market trends. What sets Forloop apart is its unique no-code and Python-first hybrid philosophy, which ensures that while the initial setup is accessible to non-engineers, the output remains robust and extensible for technical users. Unlike cloud-only tools, its current desktop-based execution offers a high level of privacy and local control, which is often a priority for security-conscious firms. Furthermore, users have reported reducing the time needed to deploy AI models by nearly half by using the platform to continuously clean and transform data. While the user interface is still evolving, the core functionality offers a powerful alternative to manual data science work.
Pros & Cons
Supports both no-code and Python-first workflows for maximum flexibility.
Reduces time spent on data engineering by up to 120 hours per person monthly.
Offers a free tier with 1,000 API requests for community users.
Capable of cutting AI model deployment time by up to 45%.
High privacy standards provided by its desktop-first application approach.
The user interface and user experience are noted by users as needing improvement.
The cloud version of the platform is currently unavailable and marked as coming soon.
API requests are capped on all non-enterprise tiers, which may limit high-volume users.
Users are currently limited to local desktop environments on Windows or Mac.
Use Cases
Data scientists can automate the continuous cleaning and transformation of datasets, reducing the time to deploy AI models to production.
Real estate firms can connect multiple property websites to their internal systems to automate market tracking and routine data collection.
FMCG companies can gather external market data to adapt pricing strategies and track competitive changes in real-time.
Growth hackers can build automated data delivery pipelines to fuel lead generation and market research without coding knowledge.
Data engineers can use the Python-first backend to create production-ready pipelines while allowing analysts to use the no-code interface.
Platform
Task
Features
• no-code workflow builder
• automated data cleaning
• collaborative team workspaces
• desktop application (windows/mac)
• concurrent data pipelines
• api request management
• web scraping automation
• python-first integration
FAQs
Is there a free version of Forloop available?
Yes, Forloop offers a Community plan that is free to use. It includes 1,000 API requests per month, support for 3 concurrent pipelines, and access to community-based support.
Which operating systems does the Forloop app support?
Forloop is currently a desktop application available for Windows and macOS. The company has stated that a cloud version of the platform is currently under development.
Can I collaborate with others on my data pipelines?
Collaboration is available on all paid plans, starting with 3 collaborators on the Hobby plan and extending to unlimited collaborators on the Team and Enterprise plans.
Does Forloop offer help with setting up complex scrapers?
Yes, Forloop provides implementation and dedicated services for teams who do not have the time to set up their own data or scraping processes manually.
How many API requests are included in the Pro plan?
The Pro plan includes 100,000 API requests per month. It also features unlimited concurrency and a dedicated onboarding session to help your team get started.
Pricing Plans
Hobby
USD29.00 / per month• 20,000 API requests
• 10 Concurrent pipelines
• Up to 3 collaborators
• Community support
Pro
USD99.00 / per month• 100,000 API requests
• Unlimited Concurrency
• Up to 10 collaborators
• Team support (email, slack, discord)
• Dedicated onboarding session
Team
USD299.00 / per month• 500,000 API requests
• Unlimited Concurrency
• Unlimited collaborators
• Team support (email, slack, discord)
• Dedicated onboarding session
Community
Free Plan• 1,000 API requests
• 3 Concurrent pipelines
• Sharing of pipelines
• Community support
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
No ratings available yet. Be the first to rate this tool!
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