Extract web data into structured JSON, no scraper required.
Tabstack is a managed web API that serves as a structured data extraction API, enabling developers to extract data, get cited answers, and automate browser tasks with a single call. It is designed for engineers building data pipelines, AI agents, or automation workflows who want to avoid managing LLMs, browsers, or scraping infrastructure. The core value is simplicity: pass a URL, a schema, a question, or a task, and receive structured JSON, synthesized reports, or completed browser actions within minutes. The platform is Mozilla-backed, ensuring data privacy and responsible handling. With 10,000 free credits to start, it lowers the barrier to integrating web data capabilities.
The primary pain point Tabstack solves is the complexity and fragility of building web data extraction systems. Traditionally, extracting structured information from websites requires orchestrating headless browsers, writing custom scrapers that break when sites change, managing proxy rotations, and wiring LLMs to parse unstructured content. This overhead diverts engineering time from core product features and often results in brittle pipelines that fail silently. For teams building competitive intelligence dashboards, lead enrichment tools, or research agents, these maintenance burdens delay time-to-market and increase operational costs. Tabstack eliminates this entire layer by handling reasoning, rendering, and schema enforcement server-side, so developers can focus on shipping features rather than maintaining data infrastructure.
The first major feature group is the /extract/json endpoint, which enables schema-matched JSON extraction from any public URL. Developers define a JSON schema specifying the fields they need—such as product name, price, and size availability—and call the endpoint with the target URL. The API returns data that conforms exactly to that schema, one level deep. Because the reasoning and rendering happen on Tabstack’s side, there is no need to manage a browser or parse HTML. This feature is especially useful for pricing comparison, inventory tracking, and content aggregation, where structured data is required for downstream analysis or dashboards. The endpoint supports multiple data types and nested objects, as shown in the Nike sneaker example.
A second core capability is the /research endpoint, which provides cited answers from the live web in a single API call. Developers submit a natural language query, and Tabstack selects relevant sources, reads their content, synthesizes an answer, and returns it with inline citations linking back to each source. The results can be streamed over Server-Sent Events (SSE), enabling real-time display in user interfaces. This endpoint is designed for in-product research features where accuracy and provenance are critical, such as financial risk analysis or market research. By delivering attributed answers, it builds user trust and eliminates the need to build a multi-step research pipeline that includes search, retrieval, and LLM summarization.
Publisher
A
admin
Launch Date2026-06-12
Pricingfree
Domain Authority
Ahrefs DR55/100