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.
Best use case
ai-cost-estimator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using ai-cost-estimator should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/afrexai-ai-cost-estimator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ai-cost-estimator Compares
| Feature / Agent | ai-cost-estimator | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# AI 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/
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