Bulkgpt provides an AI automation platform that lets users chain web scraping, search enrichment, and AI generation into repeatable workflows without coding. It supports batch processing of thousands of rows, enabling use cases such as SEO content creation, research, outbound outreach, and content operations, and includes tools for generating articles, metadata, and structured data from keyword lists. The platform emphasizes scalability, handling large automation challenges while saving significant time for users.
Funding
Funding not disclosed
Founders
Product
Problem
Businesses that need large volumes of SEO articles, research reports, or outreach content must manually combine web scraping, data enrichment, and AI text generation, which is time‑consuming, error‑prone, and requires programming expertise.
Solution
Bulkgpt provides a no‑code visual workflow builder that lets users chain web scraping, search‑based enrichment, and AI generation into repeatable pipelines. Users import data from CSV, JSON, or Google Sheets, and the platform processes thousands of rows in parallel, automatically producing articles, metadata, and structured content. The system handles batch execution, scaling to millions of records while tracking progress and delivering results in a unified dashboard. By automating the entire content creation chain, Bulkgpt reduces manual effort and accelerates SEO, research, and outbound operations.
Target Audience
Primary users are content teams, SEO agencies, and market research groups that need to produce high‑volume, data‑driven content without developer resources.
Features
- Drag‑and‑drop workflow editor that links web scraping, search enrichment, and AI text generation without coding
- Batch processing engine capable of handling thousands of rows and millions of records in a single run
- Native connectors for CSV, JSON, and Google Sheets to import and transform source data at scale
- Built‑in SEO content modules that generate articles, metadata, and structured data directly from keyword lists
- Automated data enrichment using live search results to provide contextual information for AI models
- Real‑time monitoring dashboard with execution logs, error handling, and result export options