Wax

A sub-millisecond on-device RAG memory library for iOS and macOS AI agents, implemented in pure Swift with hybrid BM25 + HNSW vector search, local MiniLM embeddings, Metal GPU acceleration, token budgeting, and a single portable .wax file format — no server or API required.

Evaluated Mar 01, 2026 (50d ago) v0.1.8
Homepage ↗ Repo ↗ Memory Storage swift rag vector-search apple-silicon metal bm25 hnsw on-device ios macos memory mcp
⚙ Agent Friendliness
79
/ 100
Can an agent use this?
🔒 Security
80
/ 100
Is it safe for agents?
⚡ Reliability
N/A
Not evaluated
Does it work consistently?
AF Security Reliability

Best When

You are building a native iOS or macOS app that needs fast, private, on-device memory/RAG without any network calls or server infrastructure.

Avoid When

You need a cross-platform, server-hosted, or cloud-scalable vector database — use Pinecone, Weaviate, Qdrant, or Chroma instead.

Use Cases

  • Persistent, searchable memory for iOS and macOS AI agent apps without cloud dependencies
  • Privacy-first RAG where all embeddings and retrieval happen on-device
  • Token-budget-aware context compression for constrained LLM context windows
  • Embedding Apple Silicon GPU acceleration into Swift AI applications via Metal

Not For

  • Cross-platform or server-side RAG systems (Swift/Apple platform only)
  • Large-scale document corpora exceeding single-device storage
  • Teams not working in Swift or the Apple ecosystem

Alternatives

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Scores are editorial opinions as of 2026-03-01.

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