everyrowdocs
Overview
  • Installation
  • Getting Started
  • API Key
  • Skills vs MCP
  • Chaining Operations
  • GitHub
API Reference
  • dedupe
  • merge
  • rank
  • agent_map
  • screen
Guides
  • How to Add A Column to a DataFrame with Web Research
  • How to Classify and Label Data with an LLM in Python
  • Remove Duplicates from ML Training Data in Python
  • Filter a Pandas DataFrame with LLMs
  • How to Fuzzy Join DataFrames in Python
  • How to sort a dataset using web data in Python
  • How to resolve duplicate rows in Python with LLMs
Case Studies
  • Build an AI lead qualification pipeline in Python
  • Fuzzy join two Pandas DataFrames using LLMs
  • Fuzzy match and merge contact lists in Python
  • How to filter job postings with LLM Agents
  • How to merge datasets without common ID in Python
  • How to score and prioritize leads with AI in Python
  • How to Screen Stocks in Python with AI Agents
  • How to use LLMs to deduplicate CRM Data
  • LLM-powered Merging at Scale
  • LLM-powered Screening at Scale
  • Python Notebook to screen stocks using AI Agents
  • Run 10,000 LLM Web Research Agents
  • Score and rank leads without a CRM in Python
  • Use LLM Agents to research government data at scale
everyrowby futuresearch
by futuresearch

Guides

Practical walkthroughs that show you how to use everyrow for common data processing tasks. Each guide covers a single operation end-to-end with working code.

Screen

  • Filter a DataFrame with LLMs

Rank

  • Sort a Dataset Using Web Data

Dedupe

  • Remove Duplicates from ML Training Data
  • Resolve Duplicate Entities

Merge

  • Fuzzy Join Without Matching Keys

Research

  • Add a Column with Web Lookup
  • Classify and Label Data with an LLM