feat: add GenesysCX study and fix Streamlit chart key collisions

- 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

studies/202512_GenesysCX/ctm-token-calculator/tokencalc/meters.py

@@ -0,0 +1,87 @@
+"""
+Genesys AI Experience token meters and pricing.
+
+Every meter carries a :class:`Confidence` flag so the UI can distinguish
+published Genesys rates from estimates and unknowns. Rates here are
+*planning inputs* — this tool explicitly does not replace contractual
+pricing (see README, Non-Goals).
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from enum import Enum
+
+
+class MeterType(Enum):
+    PER_USER_PER_MONTH = "per_user_per_month"
+    PER_INTERACTION = "per_interaction"
+    PER_MINUTE = "per_minute"
+    PER_MESSAGE = "per_message"
+    PER_SUMMARY = "per_summary"
+
+
+class Confidence(Enum):
+    CONFIRMED = "confirmed"  # published Genesys rate
+    ESTIMATED = "estimated"  # reasonable industry assumption
+    UNKNOWN = "unknown"      # rate not yet sourced
+
+    @property
+    def icon(self) -> str:
+        return {"confirmed": "🟢", "estimated": "🟡", "unknown": "🔴"}[self.value]
+
+
+@dataclass
+class TokenMeter:
+    """One Genesys AI feature's token meter.
+
+    ``units_per_token`` and ``tokens_per_unit`` are inverses; both are
+    stored because the UI shows whichever reads more naturally (e.g.
+    "17 minutes per token" vs "0.0588 tokens per minute"). For
+    PER_USER_PER_MONTH meters ``units_per_token`` is 0.0 (n/a) and
+    ``tokens_per_unit`` is the flat tokens/user/month figure.
+    """
+
+    feature: str
+    meter_type: MeterType
+    units_per_token: float
+    tokens_per_unit: float
+    confidence: Confidence
+    notes: str
+    source_url: str | None = None
+
+    def __post_init__(self) -> None:
+        if self.tokens_per_unit < 0:
+            raise ValueError(f"{self.feature}: tokens_per_unit must be >= 0")
+        if (
+            self.meter_type is not MeterType.PER_USER_PER_MONTH
+            and self.units_per_token > 0
+            and self.tokens_per_unit > 0
+        ):
+            product = self.units_per_token * self.tokens_per_unit
+            if not 0.95 <= product <= 1.05:
+                raise ValueError(
+                    f"{self.feature}: units_per_token ({self.units_per_token}) and "
+                    f"tokens_per_unit ({self.tokens_per_unit}) are not inverses"
+                )
+
+
+@dataclass
+class TokenPricing:
+    """Per-region token pricing. Default is US list at $1/token."""
+
+    region: str  # "US", "AU", "EU", "APAC"
+    list_rate_per_token: float = 1.0
+    contracted_rate_per_token: float | None = None
+    prepay_commit_tokens: int | None = None
+    overage_rate_per_token: float | None = None
+
+    def __post_init__(self) -> None:
+        if self.list_rate_per_token < 0:
+            raise ValueError(f"{self.region}: list rate must be >= 0")
+
+    def effective_rate(self, use_contracted: bool = False) -> float:
+        """Contracted rate when requested and known, else list rate."""
+        if use_contracted and self.contracted_rate_per_token is not None:
+            return self.contracted_rate_per_token
+        return self.list_rate_per_token