Forloop

About Forloop

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

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.

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

Pricing

FAQs

Ratings & reviews

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