Apple Platform Development Studio
I build production iOS and macOS apps for startups and small teams. I focus on AI-native apps that run on the device. That means fast responses, lower cloud cost, and better privacy for your users.
Technical deep dive: Swift 6 & AI integration guide series
We follow Apple standards for privacy, AI, and release quality. See Core ML, Foundation Models, App Privacy Details, and App Store Review Guidelines.
Trusted Technologies
Real systems delivered in production. From complex business platforms to developer tooling.
I work with specific types of teams and projects. Clear fit means better outcomes.
Fixed-scope services with clear outputs, clear timelines, and senior-level execution.
We review your app and show what to fix first. You get a clear roadmap, AI readiness notes, and practical next steps. Think of it like a structural survey before a renovation.
→ Prioritized technical roadmap
We build the first production version of your app in one focused sprint. You get a strong SwiftUI foundation, data sync, and an App Store-ready build. Think of it like building the frame of a house before adding rooms.
→ App Store-ready iOS/iPadOS app
We add private, on-device AI to real products. Models run locally, so your app stays fast and user data stays on the device. Think of it as hiring a smart assistant that never sends notes to an outside server.
→ Production AI feature, privacy-first
Real systems built through 3NSOFTS. Problem → System → Outcome.
Offline-First Operations Platform
Problem
SMEs juggling spreadsheets, messaging apps, and paper notes for inventory and dispatch.
System
Native iOS/iPadOS app with Core Data + CloudKit. Works offline first and syncs for smooth team collaboration.
Outcome
Single source of truth eliminated data fragmentation and communication overhead.
Developer Tool
Problem
iOS developers lose hours fixing Xcode config issues. These issues can cause build failures and App Store rejections.
System
Native macOS app that runs 9 focused checks in under 2 seconds. Analysis is read-only.
Outcome
Developers catch configuration errors before builds fail, eliminating hours of debugging.
Offline AI Assistant
Problem
Emergency scenarios require AI assistance without internet connectivity or privacy compromises.
System
100% on-device AI with Apple Intelligence, battery-aware architecture, and zero cloud dependency.
Outcome
Reliable AI guidance in offline scenarios with privacy-first design. Zero bytes sent to any server — all inference runs on-device via Apple's Neural Engine.
Industry Context
“Apple Intelligence is the personal intelligence system for iPhone, iPad, and Mac. It draws on your personal context to give you intelligence that's most helpful and relevant to you. Privacy protections are built in from the ground up.”
3NSOFTS builds production apps on this exact infrastructure. We use Apple Foundation Models, Core ML, and Apple Intelligence to ship AI features that work without cloud dependency.
Technical Differentiation
Why teams choose 3NSOFTS when they need reliable systems, not quick demos.
Your app works even when signal drops. Data saves locally first, then syncs in the background.
We run AI on the device, not in the cloud. That keeps features fast and private.
We build SwiftUI code that scales beyond a prototype. Teams can add features without rewrites.
We optimize for the next 12 months, not only for launch week.
Product Ecosystem
12+ production apps and tools designed and shipped through 3NSOFTS. Each one demonstrates a specific architectural decision in practice.
Sorto — on-device email classification using Core ML inference, zero server dependency. offgrid:AI — fully offline AI assistant with local LLM and battery-aware scheduling. Xcode Doctor — static analysis tool that finds Xcode configuration errors in under 2 seconds. CalmLedger — financial tracking with on-device data, no account required. SnipToCode — design-to-code SaaS with real-time AI streaming and Paddle billing.
These are not demos. Each is in production and distributed through the App Store or direct download. We maintain them with the same standards applied to client work.
See all products→Plain answers to the questions founders and product teams ask before starting.
Production-grade iOS, iPadOS, and macOS apps. Most projects handle complex data, offline-first workflows, and on-device AI. We do not focus on simple CRUD apps or quick prototypes.
Yes, if the product problem is defined and the team is serious about shipping. The MVP Sprint is for early-stage products that need a solid technical foundation from day one.
Software where AI is built into the core data and interaction model. It is not added later as a feature. We use on-device inference via Core ML or Apple Foundation Models, tightly integrated with the app's data layer.
The Architecture Audit delivers in 5 business days. The MVP Sprint runs 6–8 weeks. On-Device AI Integration runs 3–4 weeks. All engagements are fixed-scope and fixed-price.
On-device AI runs inference directly on the user's hardware using Apple's Neural Engine. There is no cloud round trip, and no data leaves the device. AI features work offline, respond faster, and require no API keys or ongoing cloud spend.
New engagements start with a structured application. This ensures strong product and technical alignment.
Other inquiries
For partnerships, press, or non-project inquiries: info@3nsofts.com
