# GhostFoundry-Syndicate: Hosting & AI Infrastructure Options

**Document Version:** 1.0  
**Date:** March 18, 2026  
**Audience:** Prospective customers, design partners, internal sales  

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## Executive Summary

GhostFoundry-Syndicate (GFS) is an AI-native operations platform that uses large language models (LLMs) to power its Dark Factory, agent system, and autonomous workflows. The cost of AI inference is the largest variable in operating GFS. This document outlines the deployment options available to customers, the economics behind each, and our recommended configurations.

**The bottom line:** Most customers should choose the **GFS Managed Cloud** tier. You pay a predictable monthly fee, we handle everything — hosting, AI inference, database, security, updates. No GPUs to buy, no models to manage, no DevOps headcount required.

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## Deployment Options

### Option 1: GFS Managed Cloud (Recommended)

**Who it's for:** Companies that want GFS to just work. No infrastructure management, no AI expertise required.

**What you get:**
- Full GFS platform hosted and managed by GhostFoundry
- All AI inference handled on our infrastructure (hybrid cloud + local GPU cluster)
- PostgreSQL database, managed and backed up
- SSL, CDN, automatic updates, monitoring
- 99.9% uptime SLA
- Data encrypted at rest and in transit

**What it costs:**

| Tier | Users | AI Usage | Monthly Price | Per-User Equivalent |
|------|-------|----------|--------------|--------------------|
| **Starter** | Up to 10 | Light (Dark Factory, basic agent tasks) | **$499/mo** | ~$50/user |
| **Growth** | Up to 50 | Moderate (full agent suite, autonomy system, reports) | **$1,499/mo** | ~$30/user |
| **Enterprise** | Unlimited | Heavy (Dark Factory at scale, custom agents, O2C automation) | **$3,999/mo** | Negotiated |

**What's included in the price:**
- Cloud AI inference via RouteLLM (Claude, GPT, DeepSeek, Llama — we route to the best model for each task)
- Our local GPU inference cluster handles 60-80% of routine AI calls at zero marginal cost
- Database hosting (PostgreSQL, managed, backed up daily)
- Application hosting (Next.js on managed infrastructure)
- CDN and global edge delivery
- Email notifications, integrations (Telegram, GitHub, Twilio)
- All platform updates and security patches

**Why the price is what it is:**

The biggest cost driver is AI inference. Here's the real math:

- A typical GFS user generates ~500K-2M tokens/day across agent tasks, Dark Factory requests, and autonomy workflows
- At cloud API rates ($0.40-$3.00 per million tokens depending on model), that's $0.20-$6.00/user/day in raw AI costs
- By running our own GPU inference cluster for routine tasks (simple edits, boilerplate, documentation, explanations) and only routing complex work to premium cloud models, we reduce the effective AI cost by 60-80%
- The remaining cost covers application hosting (~$50-150/mo), database (~$25-75/mo), and operational overhead

**Our infrastructure (transparent):**
- 2× NVIDIA L40S GPUs for local inference (~$1,200/mo total) — handles Qwen 3.5 35B, DeepSeek V3.2, and GLM-5 models
- Application servers on managed cloud (~$150/mo)
- PostgreSQL on managed hosting (~$50-75/mo per tenant)
- CDN and edge delivery (~$50/mo)
- Monitoring, backups, security (~$100/mo)
- Cloud LLM API budget for complex tasks (~$200-800/mo depending on usage)

**Total infrastructure cost per 50-user deployment: ~$1,800-2,500/mo**  
At $1,499/mo (Growth tier), we're pricing aggressively to build the market. Enterprise margins are healthier.

---

### Option 2: GFS Self-Hosted with Cloud AI

**Who it's for:** Companies with existing infrastructure, IT teams, or data sovereignty requirements who want to run GFS on their own servers but don't want to manage GPU infrastructure.

**What you get:**
- GFS application deployed on your infrastructure (Docker, Kubernetes, or bare metal)
- AI inference via cloud APIs (RouteLLM, OpenAI, Anthropic — your API keys)
- You manage your own PostgreSQL database
- You handle SSL, backups, monitoring
- We provide the software, updates, and support

**What it costs:**

| Component | Monthly Cost | Notes |
|-----------|-------------|-------|
| GFS License | **$299/mo** (up to 25 users) or **$799/mo** (unlimited) | Software license + updates + support |
| Cloud AI API | **$100-800/mo** | Depends on usage volume; you pay the API provider directly |
| Your hosting | **$50-300/mo** | VPS or cloud instance (4 vCPU, 8GB RAM minimum) |
| Your database | **$25-100/mo** | Managed PostgreSQL (DigitalOcean $15/mo, AWS RDS $55/mo, Supabase $25/mo) |
| **Total** | **~$475-1,500/mo** | |

**Pros:** Full control over your data, can use your existing cloud accounts, potentially lower cost for light usage.  
**Cons:** You're responsible for uptime, security, backups. AI costs are variable and unpredictable.

---

### Option 3: GFS Self-Hosted with Local AI (Maximum Cost Control)

**Who it's for:** Companies with GPU hardware (or willing to invest), technical teams, and high-volume users who want to eliminate all recurring AI costs.

**What you get:**
- Everything in Option 2, PLUS:
- Local AI inference via Ollama/vLLM running on your GPU hardware
- GFS hybrid router automatically routes simple tasks to your local models and complex tasks to cloud APIs
- You control the cost/quality tradeoff

**What it costs:**

| Component | One-Time Cost | Monthly Cost | Notes |
|-----------|--------------|-------------|-------|
| GFS License | — | **$299/mo** or **$799/mo** | Same as Option 2 |
| GPU Hardware | **$1,500-8,000** | — | RTX 4090 ($1,500) for small deployments, or A100 ($8,000) for production |
| GPU Cloud Rental (alternative) | — | **$300-1,100/mo** | L40S at $0.40-0.86/hr, A100 at $0.78-1.76/hr |
| Cloud AI API (overflow) | — | **$50-200/mo** | Only for complex tasks that exceed local capability |
| Your hosting | — | **$50-300/mo** | Application server |
| Your database | — | **$25-100/mo** | Managed PostgreSQL |
| **Total (own hardware)** | **$1,500-8,000 upfront** | **~$425-1,400/mo** | GPU pays for itself in 3-8 months |
| **Total (rented GPU)** | — | **~$725-2,200/mo** | Higher monthly but no capital outlay |

---

## Recommended Local AI Models (March 2026)

If choosing Option 3 (self-hosted with local AI), these are the models we've validated for GFS workloads:

### Tier 1: Production Recommended

**Qwen 3.5 35B** — Best overall for GFS  
- Strongest quality-to-resource ratio for code generation and multi-step agent workflows  
- 35B parameters, runs on a single RTX 4090 (24GB VRAM) with Q4 quantization  
- Outperforms many larger models on refactoring and ERP/CRM customization tasks  
- Install: `ollama pull qwen3.5:35b`  
- VRAM: ~20GB (Q4_K_M quantized)  

**DeepSeek V3.2 Speciale** — Best for math/reasoning  
- 90% on LiveCodeBench, excellent for financial calculations and reconciliation logic  
- Supports long contexts — can analyze entire modules in a single pass  
- Install: `ollama pull deepseek-v3.2`  
- VRAM: ~18GB (Q4 quantized at 35B)  

### Tier 2: Budget / Testing

**GLM-5 8B** — Lightweight but capable  
- Tops 2026 rankings for its size class on coding and reasoning  
- Runs on consumer GPUs with 6GB VRAM  
- Good for simple edits, documentation, explanations  
- Install: `ollama pull glm-5:8b`  
- VRAM: ~6GB  

**Llama 3.3 8B** — Reliable all-rounder  
- Apache 2.0 licensed, fine-tunable for domain-specific tasks  
- 72.6% on HumanEval for code generation  
- Install: `ollama pull llama3.3:8b`  
- VRAM: ~6GB  

### Tier 3: High-End (Multi-GPU)

**Qwen 3.5 72B** or **Llama 3.3 70B** — Maximum local quality  
- Near cloud-model quality for most tasks  
- Requires dual RTX 4090 or A100 80GB  
- VRAM: ~40GB (Q4 quantized)  
- Only recommended if you have the hardware and need to minimize cloud dependency  

---

## Hardware Recommendations

### For Development / Testing (1-5 Users)

| Option | Cost | Models Supported |
|--------|------|------------------|
| **Mac M2/M3/M4 Pro with 32GB unified memory** | $1,800-2,500 | Up to 35B quantized |
| **Desktop with RTX 4060 Ti 16GB** | $1,200 total build | Up to 13B quantized |
| **Desktop with RTX 4090 24GB** | $2,500 total build | Up to 35B quantized |

### For Production (10-50 Users)

| Option | Monthly Cost | Models Supported | Provider |
|--------|-------------|-----------------|----------|
| **1× L40S 48GB (cloud rental)** | $300-630/mo | Up to 35B, good throughput | RunPod, Lambda |
| **1× A100 80GB (cloud rental)** | $570-1,100/mo | Up to 70B quantized | RunPod, Lambda, AWS |
| **Own RTX 4090 + colocation** | $1,500 upfront + $100/mo colo | Up to 35B | Local datacenter |

### For Enterprise (50+ Users, High Throughput)

| Option | Monthly Cost | Models Supported | Notes |
|--------|-------------|-----------------|-------|
| **2× A100 80GB cluster** | $1,200-2,200/mo | 70B models, high concurrency | Use vLLM for production serving |
| **2× L40S 48GB** | $600-1,200/mo | Dual 35B models, good throughput | Cost-effective production |

**Important:** For production workloads serving multiple concurrent users, we recommend **vLLM** instead of Ollama. vLLM achieves up to 793 tokens/second under concurrent load vs. Ollama's ~41 TPS. Ollama is excellent for development and single-user scenarios.

---

## How the Hybrid Router Works

GFS includes a built-in intelligent routing system that automatically decides whether each AI request should go to your local model or to a cloud API. This is completely transparent to users — they never see or manage this.

### Routing Rules

| Task Type | Routes To | Why |
|-----------|-----------|-----|
| Simple edits, styling tweaks | **Local** | Fast, free, quality is sufficient |
| Boilerplate generation | **Local** | Repetitive patterns, local handles well |
| Documentation, explanations | **Local** | Low complexity, no security risk |
| Code formatting, linting suggestions | **Local** | Deterministic, no reasoning needed |
| Complex architecture decisions | **Cloud** | Requires advanced reasoning |
| Security-sensitive code | **Cloud** | Can't risk hallucinated vulnerabilities |
| Multi-file refactoring | **Cloud** | Needs large context + strong reasoning |
| Novel problem-solving | **Cloud** | Local models may hallucinate |
| Agent autonomy decisions | **Cloud** | High stakes, needs best available model |

### Automatic Fallback

If the local model is unavailable (hardware down, overloaded, or not configured), every request automatically falls back to cloud APIs. No user action required. No downtime.

### Configuration

For self-hosted deployments, activation is a single environment variable:

```bash
# In your .env file
LOCAL_LLM_ENABLED=true
LOCAL_LLM_ENDPOINT=http://your-ollama-server:11434
LOCAL_LLM_MODEL=qwen3.5:35b
```

That's it. The hybrid router handles everything else.

---

## Cost Comparison Summary

### Monthly Cost for a 25-User Deployment

| Deployment Model | Monthly Cost | AI Cost Control | Setup Complexity | Maintenance |
|-----------------|-------------|----------------|-----------------|-------------|
| **GFS Managed Cloud (Growth)** | **$1,499** | Included, predictable | None — we handle it | None — we handle it |
| **Self-Hosted + Cloud AI** | **$475-1,200** | Variable, depends on usage | Medium — deploy app + DB | You manage servers |
| **Self-Hosted + Local AI (rented GPU)** | **$725-1,500** | Controlled, mostly fixed | High — GPU + app + DB + Ollama | You manage everything |
| **Self-Hosted + Local AI (own GPU)** | **$425-900** + $2,500 upfront | Maximum control | High | You manage everything |

### Break-Even Analysis: Managed vs. Self-Hosted

For most companies, **GFS Managed Cloud pays for itself** when you factor in:
- DevOps salary for managing infrastructure: $8,000-15,000/mo (even part-time)
- Risk of downtime without 24/7 monitoring
- Time spent on model updates, security patches, GPU driver issues
- Opportunity cost of your team managing AI infrastructure instead of building product

Self-hosting only makes financial sense when:
- You're running 50+ users with heavy AI usage (>5M tokens/day)
- You already have a DevOps/ML team
- You have data sovereignty requirements that prohibit cloud AI
- You want to fine-tune models on proprietary data

---

## Recommended Hosting Providers

### For GFS Application Hosting (Self-Hosted)

| Provider | Starting Price | Why |
|----------|---------------|-----|
| **DigitalOcean** | $24/mo (4GB Droplet) | Simple, predictable pricing, great for SMBs |
| **Render** | $25/mo (Starter) | Native Next.js support, auto-deploy from Git |
| **Hetzner** | $4.50/mo (2 vCPU) | Cheapest quality hosting in EU, excellent for GDPR |
| **AWS (Lightsail)** | $20/mo (2GB) | AWS ecosystem if you need it, simple pricing |
| **Vercel** | $20/user/mo (Pro) | Best Next.js experience, expensive at scale |

### For PostgreSQL Database

| Provider | Starting Price | Why |
|----------|---------------|-----|
| **DigitalOcean Managed DB** | $15/mo | Simple, included backups, reliable |
| **Supabase** | $25/mo (Pro) | PostgreSQL + extras (auth, storage, realtime) |
| **Neon** | Free tier available | Serverless, scales to zero, branching |
| **AWS RDS** | $55/mo | Enterprise-grade, Multi-AZ available |

### For GPU Inference (Self-Hosted AI)

| Provider | GPU | Hourly Rate | Monthly (24/7) | Why |
|----------|-----|------------|----------------|-----|
| **RunPod** | L40S 48GB | $0.86/hr | ~$628/mo | Best price-performance for inference |
| **Lambda Labs** | A100 80GB | $1.79/hr | ~$1,307/mo | Reliable, good for production |
| **RunPod** | A100 80GB | $1.39/hr | ~$1,015/mo | Cheaper A100, community cloud |
| **Vast.ai** | A100 80GB | $0.50-0.80/hr | ~$365-584/mo | Cheapest, but interruptible |

---

## Quick-Start Recommendation

**If you're evaluating GFS:**  
→ Start with **GFS Managed Cloud (Starter)** at $499/mo. No setup, no infrastructure, no risk. Upgrade or migrate later.

**If you're a technical team that wants control:**  
→ **Self-Hosted + Cloud AI** (Option 2). Deploy on DigitalOcean ($24/mo) + Supabase ($25/mo) + your own RouteLLM API key. Total: ~$350-600/mo.

**If you're optimizing for minimum ongoing cost:**  
→ **Self-Hosted + Local AI** (Option 3). Buy an RTX 4090, install Ollama, set `LOCAL_LLM_ENABLED=true`. AI costs drop to near-zero for 70% of requests.

**If you're enterprise with compliance needs:**  
→ Contact us for a custom **GFS Enterprise** deployment. On-prem, air-gapped, or hybrid — we'll design it with you.

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## Questions?

Email: ghostfoundrysyndicate@outlook.com  
Website: https://spookysoftwaresyndicate.com  
Design Partner Program: https://spookysoftwaresyndicate.com/#design-partner

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*This document reflects pricing and model availability as of March 2026. Cloud AI pricing continues to decline rapidly — we update our managed tier pricing quarterly to pass savings through to customers.*

🕷️🖤
