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