Robert Helewka
64fb83257d
- Add 202512_GenesysCX TEI study (config, seed data, notebooks, README) with NPV $10.8M / ROI 266% including AI-token cost line - Add explicit `key` parameter to all chart wrappers in app/components to prevent StreamlitDuplicateElementId errors when the same figure type renders across Summary/Benefits/Costs tabs - Render benefits bar and cost pie charts on their respective tabs - Add benefits_vs_costs_by_year chart wrapper
83 lines
3.4 KiB
Markdown
83 lines
3.4 KiB
Markdown
# CTM Token Calculator
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**Genesys AI Token Cost & Business Case Calculator** — interactive,
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defensible modeling of Genesys Cloud **CX 3** platform + AI feature costs
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against realistic benefit scenarios, replacing single-point vendor ROI
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outputs with sensitivity-aware **Floor / Realistic / Stretch** analysis.
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> ⚠️ **Planning tool.** Uses published Genesys list rates unless overridden —
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> explicitly not a replacement for contractual pricing. No Genesys API
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> integration; this is a forward-looking model, not a production-consumption
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> dashboard.
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## CTM context
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- 9 sites (NAM, EMEA, AUZ, 6× APAC), **2,088 contracted named users**
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- NAM volumes from CTM discovery; **all other site data is estimated —
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confirm with CTM** (flagged throughout the UI)
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- Cost takeouts include the NICE IEX (NAM) retirement placeholder ($1.3M/yr,
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estimated)
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- Every meter carries a confidence flag: 🟢 confirmed (published rate) ·
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🟡 estimated · 🔴 unknown (working default, rate not yet sourced)
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## Install & run
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```bash
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cd ctm-token-calculator
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python -m venv .venv && source .venv/bin/activate
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pip install -r requirements.txt
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# Streamlit app (7 pages: Inputs → Export)
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streamlit run app/streamlit_app.py
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# JupyterLab notebook variant (same numbers, same library)
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jupyter lab notebooks/ctm_token_calculator.ipynb
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# Tests
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pytest
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```
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## Architecture
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All math lives in the pure-Python `tokencalc/` library; the notebook and
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Streamlit app are thin presentation layers calling the same functions —
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Run-All in the notebook produces identical headline numbers to the app on
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default inputs.
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| Module | Purpose |
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|---|---|
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| `meters.py` | Token meter + pricing dataclasses, confidence enum |
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| `defaults.py` | Genesys meter catalogue, CTM sites/takeouts/phasing, CX 3 rate ($111.28/user/mo) |
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| `inputs.py` | Validated input dataclasses (sites, feature scopes, takeouts) |
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| `scenarios.py` | Floor/Realistic/Stretch + benefit params (Genesys claim vs pressure-tested) |
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| `cost_model.py` | Platform, per-user AI, consumption AI cost engines |
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| `benefit_model.py` | AHT/ACW/email/deflection/STA benefit engines |
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| `business_case.py` | 3-year P&L, NPV @ 8%, payback, ROI |
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| `exports.py` | Multi-sheet Excel, CSV, JSON scenario save/load |
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### Correctness rules encoded in the model
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1. **Agent Copilot covers Supervisor AI Summary** — AI Summary & Insights is
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never billed at sites where Copilot is enabled (Copilot's 40 tokens/user/mo
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includes summarization). Implemented and tested.
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2. **Billing-style rounding** — monthly consumption token totals are rounded
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up (`ceil`) per site before pricing; per-user totals are exact.
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3. **Regional pricing** — every site resolves its token rate through its
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pricing region (US/EU/AU/APAC); nothing is hardcoded to US.
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4. **Adoption ramp** — consumption features ramp (default Y1 = 70%); per-user
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licences are paid in full from their phase year. Phasing is per-site,
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per-feature, per-phase (1/2/3/off).
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### Verified reference numbers
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- STA: 2,088 users × 30 tokens × 12 × $1 = **$751,680** ✓ (test)
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- Agent Copilot: 2,088 × 40 × 12 × $1 = **$1,002,240** ✓ (test)
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- NPV hand-check: 100/yr × 3 @ 8% = 257.710 ✓ (test)
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## Auditability
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Every number traces to an input and a meter: cost rows carry the feature,
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scope (sites), and confidence; benefit rows carry the driver line and scope;
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the Excel export includes input, meter, cost-detail, benefit-detail, business
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case, and three-scenario comparison sheets.
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