What to include in your ai consulting proposal template
- Use case discovery and prioritization
- Build vs buy vs fine-tune analysis
- Model selection (OpenAI vs Anthropic vs open source)
- Cost projections (token usage, infrastructure)
- Data security and compliance review
- Prompt engineering and evaluation framework
- Integration scope (existing tools, APIs)
- Ongoing monitoring and prompt iteration
How to price it
AI consulting: $5K-$25K (initial assessment + roadmap), $25K-$150K (proof of concept + measurement), $150K+ (production deployment). Hourly: $300-$800/hr. Avoid hourly for novices ā they don't understand the value.
Common mistakes to avoid
- Promising 'AI will do X' without measuring baseline
- Including ongoing token costs in your fee (variable, unbounded)
- Skipping the eval framework (you can't iterate without it)
- Vague success criteria ā clients claim AI 'didn't work'
- Not addressing data privacy upfront (legal blocker)
Sample template content
Here's an example of what a complete proposal looks like for this niche. Use it as a starting point ā you'll fill in your own details when you create one.
Frequently asked questions
āø Should I include API token costs in my fee?
No. Token costs are variable and can spike. Pass through to client at cost. Set up your own consultancy account for development and bill separately.
āø Build, buy, or fine-tune?
Buy (existing tools) for 70% of use cases. RAG over existing models for 25%. Fine-tuning for the last 5% where you have unique data + scale to justify.
āø How do I handle hallucinations?
Eval framework + RAG + temperature controls + 'I don't know' fallbacks. Build evals BEFORE prompting. Set acceptable error rate explicitly with client.
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