Claude 55dcfe330c feat(edge): Add Plaid local learning system for browser-based financial intelligence ... Implements a privacy-preserving financial learning system that runs entirely in the browser using WebAssembly. Key features: - PlaidLocalLearner: Browser-local ML engine with IndexedDB persistence - Q-learning for budget optimization and spending recommendations - HNSW vector index for semantic transaction categorization - Spiking neural network for temporal pattern recognition - Anomaly detection for unusual transaction flagging - Zero data exfiltration - all learning stays client-side Components: - examples/edge/src/plaid/mod.rs: Core Rust learning algorithms - examples/edge/src/plaid/wasm.rs: WASM bindings for browser - examples/edge/pkg/plaid-local-learner.ts: TypeScript API wrapper - examples/edge/pkg/plaid-demo.html: Interactive demo page - examples/edge/docs/plaid-local-learning.md: Comprehensive documentation Privacy guarantees: - Financial data never leaves the browser - Optional AES-256-GCM encryption for IndexedDB storage - User can delete all data instantly - No analytics, telemetry, or tracking		2026-01-01 17:48:00 +00:00
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plaid-local-learning.md	feat(edge): Add Plaid local learning system for browser-based financial intelligence	2026-01-01 17:48:00 +00:00