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docs: add AI cost analysis

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      COST_ANALYSIS.md

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COST_ANALYSIS.md

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# AI Cost Analysis
## Model Used
**Claude claude-sonnet-4-5** (`claude-sonnet-4-5-20251001`)
---
## Per-Request Cost Breakdown
### Token Assumptions
| Component | Tokens | Notes |
| ---------------------------------- | ---------- | --------------------------------------------- |
| System prompt | ~800 | Tool registry + citation rules + instructions |
| Conversation history (avg 3 turns) | ~200 | Rolled-up prior messages |
| User message | ~100 | Average query length |
| Tool call result | ~300 | Structured JSON from tool |
| **Total input** | **~1,200** | |
| Response generation | **~400** | Typical financial explanation |
### Claude Sonnet Pricing
| Token Type | Rate | Cost per Request |
| ------------------- | ------------------ | ------------------------------- |
| Input | $3.00 / 1M tokens | 1,200 × $0.000003 = **$0.0036** |
| Output | $15.00 / 1M tokens | 400 × $0.000015 = **$0.006** |
| **Total per query** | | **$0.0096 ≈ $0.01** |
---
## Development & Testing Costs
### Development Estimate
| Activity | Queries | Cost |
| ------------------------------------------- | ---------- | -------- |
| Agent prototyping (classify, route, format) | ~500 | ~$5.00 |
| Tool development + debugging | ~600 | ~$6.00 |
| Eval suite creation + validation | ~400 | ~$4.00 |
| UI integration + end-to-end testing | ~300 | ~$3.00 |
| Deployment + final polish | ~200 | ~$2.00 |
| **Total estimated development** | **~2,000** | **~$20** |
### Infrastructure Costs (Development)
| Service | Cost |
| ------------------------ | ------------------------------- |
| LangSmith | Free tier (10,000 traces/month) |
| Railway deployment | Free tier (sufficient for MVP) |
| **Total infrastructure** | **$0** |
### Total Development Cost
**~$20** (API calls only)
---
## Production Cost Projections
### Assumptions
- 5 queries per user per day (realistic for a personal finance assistant)
- 1,600 tokens average per query (input + output with tool call overhead)
- 1.2× multiplier for tool call metadata overhead
- Effective cost per query: **$0.012** (after overhead)
### Scale Projections
| Scale | Monthly Users | Daily Queries | Monthly Queries | Monthly API Cost |
| ---------- | ------------- | ------------- | --------------- | ---------------- |
| Starter | 100 | 500 | 15,000 | **~$18** |
| Growth | 1,000 | 5,000 | 150,000 | **~$180** |
| Scale | 10,000 | 50,000 | 1,500,000 | **~$1,800** |
| Enterprise | 100,000 | 500,000 | 15,000,000 | **~$18,000** |
### Cost Per Feature
| Feature | Avg Input Tokens | Avg Output Tokens | Cost/Query |
| ---------------------------- | ---------------- | ----------------- | ----------- |
| Portfolio analysis | 1,000 | 400 | ~$0.009 |
| Property tracking (CRUD) | 600 | 200 | ~$0.005 |
| Strategy simulation | 1,400 | 600 | ~$0.013 |
| Life decision advisor | 1,600 | 800 | ~$0.016 |
| Wealth gap visualizer | 900 | 300 | ~$0.008 |
| Relocation runway | 1,200 | 500 | ~$0.011 |
| Family planner | 1,100 | 450 | ~$0.010 |
| **Average across all tools** | **1,114** | **464** | **~$0.010** |
---
## Cost Optimization Strategies
### 1. Query-Level Caching (saves ~30%)
Common queries like "Austin market data", "Federal Reserve benchmarks", and "What is my portfolio?"
can be cached with a 24-hour TTL. This reduces repeat Claude API calls for identical inputs.
- Estimated savings at 1,000 users: ~$54/month
- Implementation: Redis or simple in-memory LRU cache
### 2. Model Tiering (saves ~70% on classification)
Use Claude Haiku for the classify_node (~10x cheaper than Sonnet) and reserve Sonnet only for
the format_node where response quality matters.
- Classification cost with Haiku: ~$0.0003/request (vs $0.003 with Sonnet)
- Saves: $0.0027 per request × 15,000/month = ~$40/month at Starter tier
### 3. Conversation Compaction (saves ~20%)
Summarize conversation history older than 3 turns instead of sending raw messages.
This reduces input tokens for multi-turn conversations from ~800 to ~200.
- Savings: 600 tokens × $0.000003 × 15,000/month ≈ $27/month at Starter
### 4. Tool Result Truncation (saves ~10%)
Real estate listings and portfolio data can be pre-summarized before LLM formatting.
Reduces average output from 400 to 300 tokens for data-heavy responses.
### Combined Optimization Impact
At 1,000 users/month, implementing all 4 strategies reduces cost from ~$180 to ~$85/month —
a **53% reduction**.
---
## Break-Even Analysis
### SaaS Pricing Model
| Subscription Price | Monthly Cost at 1,000 users | Gross Margin |
| ------------------ | --------------------------- | -------------------------------- |
| $9.99/month | $180 API + $0 infra | **55%** (with optimization: 91%) |
| $14.99/month | $180 API + $0 infra | **70%** (with optimization: 94%) |
| $19.99/month | $180 API + $0 infra | **78%** (with optimization: 96%) |
At **$15/month** subscription and 150 queries/month per user:
- Revenue per user: $15.00
- API cost per user: $0.18 (150 × $0.012)
- Gross margin: **98.8%** before infrastructure and support
### When to Pay for Infrastructure
| Milestone | Infrastructure Needed | Estimated Monthly Cost |
| --------------- | ------------------------------------ | ---------------------- |
| 0–500 users | Railway free tier + LangSmith free | $0 |
| 500–5,000 users | Railway $5 + LangSmith Developer $39 | $44/month |
| 5,000+ users | Railway Pro $20 + LangSmith Plus $99 | $119/month |
---
## Observability Cost
| Tool | Plan | Cost |
| ---------------------- | -------------------------- | ------------ |
| LangSmith | Free (10,000 traces/month) | $0 |
| Railway | Free tier | $0 |
| **Total at MVP scale** | | **$0/month** |
LangSmith free tier covers ~333 traced requests/day — sufficient for beta testing and
submission demo. Production would require the Developer plan at $39/month.
---
## Summary
| Phase | Monthly Cost |
| -------------------------------- | ------------- |
| Development (one-time) | ~$20 total |
| MVP (100 users) | ~$2 API |
| Early stage (1,000 users) | ~$18–$180 API |
| Growth (10,000 users, optimized) | ~$900 API |
| Infrastructure at scale | ~$120/month |
The model is **profitable from day one** at any subscription price above $1/month per user.
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