explaingit

s2fcore/s2f-lead-commander-core

Analysis updated 2026-05-18

1PythonAudience · ops devopsComplexity · 5/5LicenseSetup · hard

TLDR

S2F-Core is a self-hosted pipeline that scrapes public business data, uses a local AI model to qualify B2B sales leads, and sends timezone-aware outbound email campaigns, all without paid third-party APIs.

Mindmap

mindmap
  root((s2f core))
    What it does
      B2B lead harvesting
      AI lead qualification
      Multi channel outreach
    Tech stack
      Python
      PostgreSQL
      Docker
      Ollama Qwen2.5
    Use cases
      Source public leads
      Filter with local AI
      Scheduled email campaigns
    Requirements
      Linux server
      8GB RAM minimum
      Docker Compose

Code map

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What do people build with it?

USE CASE 1

Automatically source and qualify B2B leads from public web data without paying for a commercial scraping service.

USE CASE 2

Run a local AI model to filter out irrelevant leads and competitors before contacting anyone.

USE CASE 3

Send scheduled outbound emails that respect recipient time zones and include opt-out options.

What is it built with?

PythonPostgreSQLDockerOllamaQwen2.5

How does it compare?

s2fcore/s2f-lead-commander-core0xustaz/streamgatea-bissell/unleash-lite
Stars111
LanguagePythonPythonPython
Setup difficultyhardhardhard
Complexity5/54/54/5
Audienceops devopsdeveloperresearcher

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1day+

Requires a dedicated Linux server with 8GB+ RAM, Docker Compose, a PostgreSQL database, and a local Ollama model, multiple services must be configured together.

The README does not provide an open source license, the author describes core components as proprietary and owned by the company, so reuse rights are unclear.

In plain English

S2F-Core is a self-hosted software pipeline built to automatically find and reach out to potential business customers, specifically athletic brands, sports clubs, and training centers, on behalf of its owner, a sportswear manufacturer in Sialkot, Pakistan. Rather than paying for commercial lead generation or scraping services, the whole system runs on hardware you own, using free local tools instead of paid APIs. The pipeline works in stages. First, it gathers public business information such as emails, phone numbers, and social media profiles from sources including Google Maps and search results. Next, it uses a locally run AI language model, Qwen2.5, to judge whether each lead is actually relevant to the business, filtering out competitors, directories, and other bad matches. Qualified leads are then sorted into different outreach queues depending on whether an email address, a social profile, or neither was found. Finally, a scheduling component sends outbound emails only during business hours in the recipient's own time zone, rotating between several email delivery services and including reply options such as interested, later, and unsubscribe. The system uses several techniques to keep working when a target website tries to block automated access, including routing some requests through the Tor network and automatically rotating its network identity if a connection is blocked. Phone numbers collected are standardized into international format using Google's phone number library. The project runs as a set of services connected to a shared PostgreSQL database, and is designed to run on a Linux server, specifically Debian or Ubuntu, with at least 8 gigabytes of memory and four CPU cores. Setup involves creating directories, initializing the database schema from a provided SQL file, and starting supporting services such as the database and a headless browser through Docker Compose. The README does not state an open source license, and the project describes its core crawling and validation components as proprietary technology owned by the author and his company.

Copy-paste prompts

Prompt 1
Help me set up the PostgreSQL schema for S2F-Core using the provided schema.sql file.
Prompt 2
Walk me through starting the Docker Compose services for S2F-Core's database and headless browser.
Prompt 3
Explain how S2F-Core's Qwen2.5 qualification step decides whether a lead is relevant.
Prompt 4
What hardware and OS does S2F-Core require to run reliably?

Frequently asked questions

What is s2f-lead-commander-core?

S2F-Core is a self-hosted pipeline that scrapes public business data, uses a local AI model to qualify B2B sales leads, and sends timezone-aware outbound email campaigns, all without paid third-party APIs.

What language is s2f-lead-commander-core written in?

Mainly Python. The stack also includes Python, PostgreSQL, Docker.

What license does s2f-lead-commander-core use?

The README does not provide an open source license, the author describes core components as proprietary and owned by the company, so reuse rights are unclear.

How hard is s2f-lead-commander-core to set up?

Setup difficulty is rated hard, with roughly 1day+ to a first successful run.

Who is s2f-lead-commander-core for?

Mainly ops devops.

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