CRM Automator: Modular Agentic CRM Toolkit

Author: Trung Le
Team: RealTimeX.ai
Repository: https://github.com/therealtimex/crm-automator

Overview

The CRM Automator is a modular, agentic toolkit designed to transform unstructured data (emails, transcripts, documents) into structured CRM records. Unlike monolithic automation scripts, this toolkit is built as a collection of reusable Tools that can be orchestrated by AI agents or run as standalone pipelines.

Current Status: Production-Ready (v2.0)

Key Features

  • 🧩 Modular Architecture: Decoupled Ingestion (EML/Text), Intelligence (LLM Extraction), and Integration (CRM Sync).
  • 🤖 Agent-Ready: Components like IntelligenceLayer and RealTimeXClient are designed to be imported as tools for frameworks like LangChain or Autogen.
  • 🛡️ Idempotent & Safe: Implements "Search-before-Update" patterns and SQLite-based state tracking to prevent duplicate records.
  • 🧹 Smart Cleaning Pipeline: Automatically converts bloaty HTML into clean Markdown, strips noise, and resolves tracking links (e.g., unwraps Proofpoint/Safelinks and resolves HubSpot redirects) to ensure accurate URL extraction.
  • 🧠 OpenAI-Compatible: Works independently with OpenAI, Anthropic, or local LLMs (via LM Studio/Ollama) using instructor.

Installation

  1. Clone the repository:

    git clone https://github.com/therealtimex/crm-automator.git
cd crm-automator

  2. Install dependencies:

    # Option A: Standard pip
pip install -r requirements.txt

# Option B: Modern uv (Recommended)
uv sync

  3. Configure environment:

    cp .env.example .env
# Edit .env with your CRM and LLM credentials

Usage

1. Process Emails (.eml)

Run the automator on a single EML file or an entire directory recursively.

Using uvx (Fastest, zero-install):

uvx eml/eml_automator.py "path/to/email.eml" --env-file ".env"

Using a directory:

uv run python eml/eml_automator.py "path/to/directory" --env-file ".env"

Options:

  • --force, -f: Force re-processing of an email even if it was already synced.
  • --verbose, -v: Enable debug logs to see HTTP requests and LLM thought process.

2. Generic Agent Demo

See how the toolkit handles raw text (e.g., meeting transcripts):

python3 eml/agent_demo.py --api-key "your_key"

Architecture

graph TD
    Ingest[Ingestion Layer] --> Intelligence[Intelligence Layer]
    Intelligence <--> Search[Web Search Tool]
    Intelligence --> Client[CRM Client]
    Client --> CRM[(RealTimeX CRM)]
  • crm_client.py: The "hands" – handles all API calls with retries and 10s timeouts.
  • intelligence.py: The "brain" – uses Pydantic models to extract structured data from text.
  • persistence.py: The "memory" – prevents processing the same resource twice.

Built with ❤️ by the RealTimeX.ai Team

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Requires

Python >=3.10

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