README.md

metadata

title: everyrow annotate – AI Data Annotation & Web Research Agents
emoji: 🏷️
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
short_description: AI-powered data annotation powered by webresearch agents

🏷️ everyrow annotate – AI Agents for Data Annotation & Web Research

everyrow annotate is an AI-powered data annotation and enrichment tool that uses web research agents to label, verify, and enrich datasets at scale.

It’s built for teams who need scalable data annotation, evidence-backed labeling, and agentic research workflows across large datasets.

Agents are tuned on Deep Research Bench, our benchmark for questions that need extensive searching and cross-referencing.

Get your API key from everyrow.io/api-key ($20 free credit).

See everyrow.io for docs and everyrow-sdk for the GitHub repository.

🧩 What Can You Annotate with everyrow?

everyrow Annotate is designed for row-by-row labeling and enrichment, including:

• 🏷️ Data annotation – Classify companies, products, or people using web evidence
• 🌍 Web-backed labeling – Tag rows based on information found across multiple sources
• 📊 Dataset enrichment – Add funding, industry, location, or other attributes
• 🧠 AI-assisted verification – Check if claims about an entity are true
• 🔎 Research-based features – Turn unstructured web info into structured columns

If your workflow involves “add labels or attributes to every row in my dataset”, everyrow Annotate is built for you.

⚙️ How It Works

1. Upload a CSV with the rows you want to annotate
2. Write an annotation instruction (e.g., “Label each company’s industry and whether it is B2B or B2C”)
3. everyrow’s AI research agents search the web, compare sources, and extract structured labels
4. Download your annotated and enriched dataset

Unlike traditional labeling tools that rely only on human input or static models, everyrow uses live web research to support complex, evidence-based annotations.

🤖 Agentic Research at Scale

everyrow Annotate uses autonomous AI research agents that can:

• Perform multi-step web searches
• Cross-reference multiple sources
• Resolve conflicting information
• Produce structured, explainable outputs

This enables high-quality data annotation for tasks that go beyond simple classification — especially when answers require investigation, not just pattern matching.

🔌 Powered by the everyrow SDK

This demo runs on the everyrow SDK, which provides APIs for scalable AI data annotation, web research automation, and dataset enrichment.

Get an API key at everyrow.io/api-key (includes $20 free credit).

📚 Docs: everyrow.io