Local-First ยท Privacy by Design ยท Continuous Learning

Private AI.
On Your Terms.

A native, on-device AI assistant platform with embedded memory and zero cloud dependency. Your data never leaves your machine.

0 Cloud Calls
0 Telemetry
100% On-Device
โˆž Privacy

The Problem

AI assistants today require you to send every conversation, every document, and every thought to someone else's servers.

For businesses handling sensitive data โ€” legal, financial, medical, defence, IP-heavy R&D โ€” that's a non-starter. You shouldn't have to choose between powerful AI and total data privacy.

SwiftMaestro eliminates the trade-off. Full AI assistant capabilities. Zero data exfiltration. Everything runs on your hardware.

Core Capabilities

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Multi-Agent Workspace

Create named AI agents specialised for different domains โ€” coding, research, compliance, writing, operations. Each agent maintains its own context, rules, and conversation history.

โšก

Local LLM Integration

Connects to any OpenAI-compatible local model endpoint. Streaming real-time responses. Choose your model โ€” from lightweight 4B to full 70B+ depending on your hardware.

๐Ÿง 

Embedded Memory & Learning

Three native memory modules โ€” Context Store, Fact Graph, and Learning Engine โ€” built directly into the app. All stored locally in embedded SQLite with vector search. No external databases.

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Personalised Fine-Tuning

An included pipeline extracts knowledge from your conversations, distills it into training data, and fine-tunes LoRA adapters on-device. The AI improves over time based on how you work.

Memory Architecture

Context Store

Inspired by OpenViking

Hierarchical knowledge organisation with layered summaries โ€” deep context and resource memory.

Fact Graph

Inspired by Graphiti

Temporal entity-relationship tracking with validity windows โ€” knows when facts changed.

Learning Engine

Inspired by PAL

Continuously improves retrieval quality and promotes raw conversation data into structured knowledge.

Privacy & Security

The safest data is data that never leaves.

๐Ÿšซ

No Cloud

All data stays on your Mac. No cloud sync. No remote servers. No third-party API calls.

๐Ÿ“Š

Zero Telemetry

No analytics. No crash reporting. No usage tracking. We literally cannot see what you do.

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Hardware Security

Secrets stored in macOS Keychain โ€” Apple's hardware-backed security framework. Not in config files.

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Air-Gap Ready

Fully functional with zero internet. The only network call is to your own local LLM endpoint.

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Local Training

LoRA fine-tuning runs on-device using Apple Silicon. Training data never leaves your machine.

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No PII Leakage

No personally identifiable information leaves the device. By design, not by policy.

System Requirements

SwiftMaestro runs models natively on Apple Silicon via MLX. No external server required.

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Minimum

Apple M1 Ultra Mac Studio

64GB unified memory
macOS 14.0 Sonoma or later
Runs up to 35B parameter models at full speed

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Recommended

M2 Ultra / M4 Max Mac Studio

128GB+ unified memory
Runs 70Bโ€“122B parameter models
Concurrent model loading + fine-tuning

๐Ÿ”ฎ

Future Platforms

Windows & Linux ports planned

NVIDIA GPU acceleration under evaluation
Same privacy model โ€” all inference stays local
Cross-platform timeline: 5โ€“8 months

Why Apple Silicon? MLX leverages the unified memory architecture โ€” CPU and GPU share the same RAM, so a 60GB model doesn't need a 60GB GPU. This makes large-model inference practical on workstation hardware that also runs your daily apps.

Technical Architecture

โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚                    SwiftMaestro.app                    โ”‚
โ”‚                                                       โ”‚
โ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚
โ”‚  โ”‚  SwiftUI โ”‚  โ”‚      Memory Orchestrator            โ”‚ โ”‚
โ”‚  โ”‚   Chat   โ”‚โ—€โ–ถโ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ โ”‚
โ”‚  โ”‚    UI    โ”‚  โ”‚  โ”‚Context โ”‚ โ”‚ Fact  โ”‚ โ”‚ Learning โ”‚ โ”‚ โ”‚
โ”‚  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜  โ”‚  โ”‚ Store  โ”‚ โ”‚ Graph โ”‚ โ”‚  Engine  โ”‚ โ”‚ โ”‚
โ”‚       โ”‚        โ”‚  โ””โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ โ”‚
โ”‚       โ”‚        โ”‚       โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜        โ”‚ โ”‚
โ”‚       โ–ผ        โ”‚          SQLite ยท FTS5 ยท vec        โ”‚ โ”‚
โ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚
โ”‚  โ”‚   MLX    โ”‚                                         โ”‚
โ”‚  โ”‚ Inferenceโ”‚   HuggingFace Hub โ†โ†’ Local Model Store  โ”‚
โ”‚  โ”‚  Engine  โ”‚        macOS Keychain (secrets)          โ”‚
โ”‚  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜                                         โ”‚
โ”‚       โ”‚  Native Apple Silicon GPU                      โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
        โ”‚  (optional fallback)
        โ–ผ  HTTP (localhost / LAN)
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚  External LLM   โ”‚
โ”‚  LM Studio /    โ”‚
โ”‚  Ollama / vLLM  โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
LanguageSwift 6.3, SwiftUI
PlatformmacOS 14.0+ (Apple Silicon native)
InferenceMLX โ€” native Apple Silicon GPU acceleration
ModelsLocal files or HuggingFace Hub download
StorageEmbedded SQLite + FTS5 + sqlite-vec
SecuritymacOS Keychain, App Sandbox compatible
DistributionSigned & notarised .dmg installer
FallbackOpenAI-compatible HTTP endpoint (optional)

Business Integration

๐Ÿ“ฆ Simple Deployment

Single installer per Mac. No IT infrastructure beyond Macs and a local model server (shared or per-seat).

๐Ÿ”’ Data Isolation

Each installation is fully self-contained. No shared databases, no cloud state. Meets strict data sovereignty requirements.

๐ŸŽ›๏ธ Model Flexibility

Choose your LLM โ€” Qwen, Llama, Gemma, Mistral โ€” hosted on-premises. Full control over capabilities and training data.

โš™๏ธ Customisation

Pre-configure agents with business-specific rules, knowledge, and workflows, then distribute to your team.

Cross-Platform Strategy

macOS-native today. Designed for portability tomorrow.

Already Platform-Agnostic

  • SQLite + FTS5 + sqlite-vec storage engine
  • OpenAI-compatible HTTP/SSE client protocol
  • Memory architecture (database patterns, not Swift-specific)
  • Upstream libraries (OpenViking, Graphiti, PAL) โ€” Python
  • Knowledge distillation & LoRA training pipeline

Cross-Platform Path

๐Ÿ”ง SwiftMaestro Core Rust or Kotlin Memory ยท LLM Client ยท SQLite
๐ŸŽ macOS โ€” SwiftUI (built)
๐ŸชŸ Windows โ€” WinUI / Tauri
๐Ÿง Linux โ€” GTK / Tauri
1โ€“2 mo Core Extraction
โ†’
2โ€“3 mo Windows Port
โ†’
2โ€“3 mo Linux Port
โ†’
5โ€“8 mo total 3-Platform Coverage
The privacy model โ€” everything local, no cloud โ€” translates directly to any platform. Cross-platform does not compromise the privacy guarantee.

Project Status

Phase 1 Complete

Native macOS app โ€” multi-agent chat, streaming, secure storage

Phase 2 In Progress

Embedded memory architecture โ€” fact graph, context store, learning engine

Phase 3 Planned

Chat pipeline integration with memory-augmented responses

Phase 4 Planned

Learning engine, knowledge promotion, maintenance workers

Phase 5 Planned

Signed/notarised distribution, App Store evaluation

Get in Touch

Interested in SwiftMaestro for your business?

Whether you're exploring private AI for your organisation, interested in integration, or want to discuss cross-platform deployment โ€” we'd love to hear from you.

hello@swiftmaestro.com