EnrichCRM

CSV in, enriched contacts out, at a fraction of the cost.

A tool that turns a spreadsheet of business emails into researched contact records at a lower cost.

Who it helps: Marketing and research operators enrich outbound lists without per-record managed-service fees, and downstream outreach runs on researched company, industry, and stack data.

language: TypeScript (Node CLI + Next.js 15)
CLI stack: Brave Search, Trafilatura, Gemini Flash
UI stack: OpenAI agents, Firecrawl, SSE streaming
storage: SQLite, per-contact cost tracking
ownership: Sole engineer: built end to end
history: built Jun 2025 to Apr 2026
repo: Private

The problem

Researching each contact’s company, industry, and tech stack by hand is slow, and managed enrichment services charge by the record. EnrichCRM treats that cost as an engineering problem: a local scraper and a cheaper model in place of the paid stack.

How it’s built

Cost treated as an engineering problem
The CLI replaces a paid scraping layer with Trafilatura (local, no per-page network round-trip) and swaps GPT-4o for Gemini Flash. Measured spend lands near $0.003 per contact in the --stats output. The broader "4.6x faster, 77% cheaper" comparison is self-reported, with no benchmark harness in the repo.
Resume-safe batch processing
Status is written to SQLite before and after every contact, so an interrupted run restarts at the exact failure point with --resume, and --retry-errors reprocesses only the failures rather than the whole list.
Multi-agent field routing on the UI path
The web surface categorizes each requested field into one of six domains and dispatches to a purpose-built agent, with cross-source confidence scoring and structured output enforced through Zod schemas.

By the numbers

$0.003 per contact on the CLI path (traceable in --stats)

4.6x faster than the managed path

self-reported

6 specialized enrichment agents on the UI path

How to read these numbers

self-reported

marks figures stated in docs or commit history that I could not reproduce from the repository alone. Every other figure is traced to code or clearly marked self-reported.

4.6x: Basis: README comparison of developer-observed runs: Firecrawl + OpenAI at 47.6s and $0.013/contact versus Trafilatura + Gemini at 10.4s and about $0.003/contact. The repo tracks CLI cost via --stats, but does not include a benchmark harness for the timing multiple.

Where this stands today

Shipped. Two enrichment surfaces (a Brave + Gemini CLI and an OpenAI + Firecrawl web UI) share types but not providers, and the README is candid about the seam. There is no spreadsheet UI and no Salesforce integration.