---
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](https://everyrow.io/), our benchmark for questions that need extensive searching and cross-referencing.

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

See [everyrow.io](https://everyrow.io/) for docs and [everyrow-sdk](https://github.com/futuresearch/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](https://github.com/futuresearch/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](https://everyrow.io/api-key)** (includes $20 free credit).

📚 Docs: **[everyrow.io](https://everyrow.io/)**