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AgenticMeadows

AgenticMeadows

AI-Powered Landscaping Field Service Management

100% local · No cloud required · No subscriptions


Quick Install · Features · Architecture · Contributing

What is AgenticMeadows?

AgenticMeadows is an open-source, AI-first field service management platform built specifically for landscaping businesses. It replaces expensive SaaS tools like Jobber and HousecallPro with a locally-hosted platform that runs entirely on your hardware.

Glen, your AI assistant, can manage your entire business through natural conversation — create clients, schedule jobs, draft quotes, analyze lawn health, and more.


One-Command Install

macOS / Linux / WSL

curl -fsSL https://raw.githubusercontent.com/GTM-Planetary/agenticmeadows/main/install.sh | bash

Manual Install (if you already have Docker)

git clone https://github.com/GTM-Planetary/agenticmeadows.git
cd agenticmeadows
docker compose up -d
# Open http://localhost:3001

Start / Stop / Update

./start.sh   # Start the app (opens browser)
./stop.sh    # Stop all services (data preserved)
./update.sh  # Pull latest + rebuild + restart

Features

Glen AI Assistant

  • Natural language CRM management — "Create a client: Jose Nunez, 208-555-1234"
  • Slash commands (/new-client, /schedule, /weather, /lawn-check)
  • Interactive entity cards with inline editing
  • Batch actions — handle multiple operations in one message
  • Fuzzy address matching — "Show me the Geneva Pl property"
  • Lawn health diagnostics from built-in knowledge base
  • Treatment recommendations with chemical, organic, and cultural options

Client & Property Management

  • Full CRM with clients, properties, and contact info
  • Property measurements (lot size, lawn area, bed area, edging)
  • Chemical application tracking with re-entry compliance
  • Property health scoring and predictive maintenance

Scheduling

  • Google Calendar-style week view with 24-hour time grid
  • Double-click to create jobs directly on the schedule
  • Click job cards for detail popout with quick actions
  • Configurable job types (Mow, Fertilize, Aeration, etc.)

Quoting & Invoicing

  • Service catalog with configurable pricing (flat, per sqft, per hour)
  • Quote builder with service dropdown auto-fill
  • Quote workflow: Draft → Sent → Approved → Convert to Invoice
  • Invoice customization with company branding
  • PDF and CSV export

Reports & Analytics

  • Revenue reports (by month, client, service type)
  • Job completion metrics and productivity tracking
  • Client revenue rankings and sales pipeline funnel
  • Invoice aging report
  • Chemical application compliance log
  • CSV and PDF export

Predictive Maintenance

  • Equipment fleet tracking (mowers, trimmers, vehicles, trailers)
  • Maintenance scheduling with automatic alerts
  • Service logging with cost tracking
  • Repair vs. replace analysis
  • Property health assessments with predicted service needs

Settings & Administration

  • Organization settings (company name, logo, address)
  • User management with roles (Admin, Technician, Viewer)
  • Invite links for easy team onboarding
  • Configurable job types
  • Custom fields and sections
  • API key management for external integrations
  • AI Agent configuration (model, tools, skills)

Security

  • NemoClaw sandbox for AI agent isolation
  • NeMo Guardrails for jailbreak/injection detection
  • PendingAction pattern — AI proposes, human confirms all writes
  • All data stays on your hardware

Architecture

Frontend (React/Vite/Nginx)  ──▶  Backend (Express/Prisma)  ──▶  PostgreSQL 16
       Port 3001                       Port 4000                    Port 5433
           │                               │
           ▼                               ▼
   AI Service (FastAPI)  ──────▶  Ollama (Qwen 3.5)
   ReAct Agent Engine              Local LLM
       Port 8000                    Port 11435

Tech Stack:

Layer Technology
Frontend React 18, Vite, TypeScript, TailwindCSS
Backend Node.js, Express, Prisma ORM
AI Service Python, FastAPI, ReAct Agent Engine
LLM Qwen 3.5 via Ollama (auto-selects model size)
Database PostgreSQL 16
Security NemoClaw + NeMo Guardrails
Agent OpenClaw with 23 MCP tools

System Requirements

Component Minimum Recommended
RAM 4 GB 16 GB+
Storage 10 GB 20 GB+
Docker 24.0+ Latest
OS macOS, Linux, Windows (WSL2) macOS Apple Silicon

The AI model auto-selects based on available RAM:

RAM Model Quality
< 4 GB Qwen 3.5 0.8B Basic
4-8 GB Qwen 3.5 2B Good
8-16 GB Qwen 3.5 4B Great
16-32 GB Qwen 3.5 9B Excellent
32 GB+ Qwen 3.5 27B Best

Optional: NVIDIA Cloud Enhancement

For better AI responses, add a free NVIDIA API key from build.nvidia.com:

  1. Go to build.nvidia.com and sign in
  2. Search for Nemotron and click "Get API Key"
  3. In AgenticMeadows: Settings → Integrations → paste key → Save

The AI will use Nemotron cloud for better responses and fall back to local Ollama when offline.


Contributing

We welcome contributions!

  1. Fork the repo
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

Apache 2.0 — see LICENSE for details.


AgenticMeadows Cloud

Coming soon — managed hosting with premium integrations:

  • QuickBooks Online sync
  • Stripe payment processing
  • SMS & email notifications (Twilio)
  • Google Calendar integration
  • Fine-tuned AI models for landscaping
  • Team GPS tracking

Built by GTM Planetary

Powered by Qwen 3.5 · OpenClaw · NemoClaw

About

AI-first landscaping field service management. Local-first with Glen AI agent, OpenClaw/NemoClaw security, Qwen 3.5 via Ollama. Open source under Apache 2.0.

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