# firecrawl/fire-enrich

🔥 AI-powered data enrichment tool that transforms emails into rich datasets with company profiles, funding data, tech stacks, and more using Firecrawl and multi-agent AI

Repository: https://github.com/firecrawl/fire-enrich
Canonical: https://ross.abutalabs.com/products/fire-enrich
Language: TypeScript
License: MIT
License Family: permissive
Last push: 2025-10-08T13:43:22+00:00

## Health v2 (maintenance only)
Score: 39/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 46, release rhythm 35, longevity 32
- inputs: {"age_days": 453, "days_push": 329, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1255, forks 314 (observed 2026-08-28T04:04:08.938546+00:00)

## What it is
Fire Enrich is an AI-powered data enrichment web application that transforms a list of email addresses into rich company datasets, including industry, funding, headcount, and tech stack details. It combines Firecrawl web scraping with OpenAI-driven multi-agent extraction, built on Next.js 15.

## Use cases
- enrich a list of emails with company profiles
- find funding stage and total raised for companies from email domains
- build lead lists with industry and employee count data
- identify tech stacks used by companies behind email addresses
- scrape and aggregate company web data automatically
- generate structured JSON datasets from raw email lists

## When to choose
- you need to turn raw email lists into structured company intelligence
- you want a self-hosted enrichment tool powered by web scraping and LLMs
- you need sourced, citation-backed enrichment results
- you want a deployable Next.js app for sales or research data enrichment

## When to avoid
- you need offline enrichment without external API dependencies
- you require bulk enrichment of millions of records at enterprise scale
- you cannot provide Firecrawl or OpenAI API keys
- you need strict data privacy since emails and scraped data pass through third-party APIs

## Facets
- artifact type: application
- maturity: active
- function: web-scraping, data-science, etl, agent-framework, llm-inference, data-generation
- domain: data-science, artificial-intelligence, analytics
- platform: self-hosted
- tags: data-enrichment, email-enrichment, nextjs, openai, firecrawl, multi-agent, company-profiling, lead-generation, automation, nodejs, web-server, docker

## Member repositories
- firecrawl/fire-enrich (main) score 39

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:08.938546+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T05:07:19.537484+00:00, confidence not recorded.
  - readme: https://github.com/firecrawl/fire-enrich (fetched 2026-08-28T04:04:08.938546+00:00, sha 3e761886a468)
- Data as of 2026-08-30T08:39:29.467469+00:00.