Skills ai-cost-estimator
Estimate infrastructure and API costs for running AI agents in production. Covers compute, API tokens, storage, and monitoring costs. Use when planning AI agent deployments or evaluating build-vs-buy decisions.
git clone https://github.com/openclaw/skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/afrexai-cto/afrexai-ai-cost-estimator" ~/.claude/skills/clawdbot-skills-ai-cost-estimator && rm -rf "$T"
skills/afrexai-cto/afrexai-ai-cost-estimator/SKILL.mdAI Cost Estimator Skill
Purpose
Help teams estimate the true cost of running AI agents in production — not just API fees, but compute, storage, monitoring, maintenance, and engineering time.
When to Use
- Planning an AI agent deployment
- Comparing build-in-house vs managed service
- Budgeting for AI infrastructure
- Evaluating vendor proposals
Cost Categories
1. Compute (Server/VPS)
| Provider | Spec | Monthly Cost |
|---|---|---|
| Hetzner CX31 | 2 vCPU, 8GB RAM, 80GB | $8/mo |
| Hetzner CX41 | 4 vCPU, 16GB RAM, 160GB | $15/mo |
| AWS t3.medium | 2 vCPU, 4GB RAM | ~$30/mo |
| AWS t3.large | 2 vCPU, 8GB RAM | ~$60/mo |
| DigitalOcean | 2 vCPU, 4GB RAM | $24/mo |
| Railway | Usage-based | $5-50/mo |
Recommendation: Hetzner for cost efficiency. AWS/GCP if client requires specific cloud.
2. LLM API Costs
| Model | Input (per 1M tokens) | Output (per 1M tokens) |
|---|---|---|
| GPT-4o | $2.50 | $10.00 |
| GPT-4o-mini | $0.15 | $0.60 |
| Claude Sonnet 4 | $3.00 | $15.00 |
| Claude Haiku | $0.25 | $1.25 |
| Llama 3.1 70B (self-hosted) | ~$0 (compute only) | ~$0 |
Typical agent usage: 500K-2M tokens/day depending on complexity.
Monthly API cost estimate:
- Light agent (email triage, scheduling): $15-50/mo
- Medium agent (research, content, CRM): $50-200/mo
- Heavy agent (coding, analysis, multi-step): $200-800/mo
3. Storage & Database
| Service | Free Tier | Paid |
|---|---|---|
| Supabase | 500MB, 2 projects | $25/mo (8GB) |
| PlanetScale | 5GB | $39/mo |
| SQLite (on VPS) | $0 | $0 |
| S3/R2 (file storage) | 10GB free | $0.015/GB |
4. Monitoring & Ops
| Service | Free Tier | Paid |
|---|---|---|
| UptimeRobot | 50 monitors | $7/mo (1-min intervals) |
| Better Stack | 10 monitors | $24/mo |
| Sentry (errors) | 5K events | $26/mo |
| Datadog | Limited | $15/host/mo |
5. Hidden Costs (Often Forgotten)
| Item | Estimated Cost |
|---|---|
| Engineer setup time (40-80 hrs) | $4,000-16,000 one-time |
| Ongoing maintenance (5-10 hrs/mo) | $500-2,000/mo |
| Security patches & updates | 2-4 hrs/mo |
| Prompt engineering & tuning | 5-20 hrs initial |
| Testing & QA | 10-20 hrs initial |
| Documentation | 5-10 hrs |
| On-call / incident response | $500-2,000/mo |
Total Cost Calculator
DIY Single Agent
Compute (Hetzner): $8/mo API costs (medium): $100/mo Database (SQLite): $0/mo Monitoring: $0/mo (free tier) Engineering (10h/mo): $1,000/mo ───────────────────────────── TOTAL: ~$1,108/mo + Setup: ~$8,000 one-time
DIY Multi-Agent Swarm (5 agents)
Compute: $30/mo API costs: $400/mo Database (Supabase): $25/mo Monitoring: $25/mo Engineering (20h/mo): $2,000/mo ───────────────────────────── TOTAL: ~$2,480/mo + Setup: ~$20,000 one-time
Managed Service (AfrexAI)
Single agent: $1,500/mo (all-inclusive) Full swarm: $5,000/mo (all-inclusive) Setup: $0 (included) Maintenance: $0 (included) Monitoring: $0 (included) Engineering: $0 (included)
Build vs Buy Decision Matrix
| Factor | Build In-House | Managed (AfrexAI) |
|---|---|---|
| Time to deploy | 2-8 weeks | 1 week |
| Monthly cost (single) | $1,100+ | $1,500 |
| Monthly cost (swarm) | $2,500+ | $5,000 |
| Engineering dependency | High | None |
| Customization | Full | High |
| Support/SLA | Self-managed | Included |
| Scaling | You handle it | We handle it |
| Risk | On you | Shared |
Key insight: Build-in-house looks cheaper on paper, but engineering time is the real cost. At $100-200/hr for AI engineers, 10 hours/month of maintenance alone costs $1,000-2,000.
ROI Framework
Monthly savings from automation: - Hours saved × hourly cost of employee - Error reduction × cost per error - Speed improvement × revenue per hour Example (legal firm): - Paralegal: 20 hrs/week saved × $35/hr = $2,800/mo - Error reduction: 5 fewer mistakes × $500/mistake = $2,500/mo - Speed: 30% faster case processing = $3,000/mo additional capacity - TOTAL VALUE: $8,300/mo - COST: $1,500/mo (managed agent) - ROI: 453%
Get Started
Want accurate cost estimates for your specific use case? → Free consultation: https://calendly.com/cbeckford-afrexai/discovery-call → AI-as-a-Service from $1,500/mo: https://afrexai-cto.github.io/aaas/landing.html → ROI Calculator: https://afrexai-cto.github.io/ai-revenue-calculator/