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iOS AI Development
& On-Device Intelligence for Startups That Ship.

I build production iOS and macOS apps for startups and small teams. My focus is AI-native apps that run entirely on the device — powered by Core ML and Apple Foundation Models. That means sub-10ms inference latency on Apple Silicon, zero per-request cloud API costs, and privacy-by-design that satisfies GDPR and CCPA without additional compliance engineering. Every project delivers production-grade Swift 6 architecture you can scale from — not a prototype that needs a full rewrite six months after launch.

Start a ProjectView Case Studies

20+

Apps shipped

5 days

Audit delivery

0 bytes

Data to servers

100%

On-device AI

BUILT ON
Swift
SwiftUI
Core ML
CloudKit
HealthKit
Foundation Models

Technical deep dive: Swift 6 & AI integration guide series · iOS AI Development Guide

We follow Apple standards for privacy, AI, and release quality — see Core ML, Foundation Models, App Privacy Details, and App Store Review Guidelines.

Systems Built

Real systems delivered in production — iOS and macOS apps now live on the App Store. Each one is built on Swift 6 and SwiftUI with Core Data, CloudKit, and on-device AI where the product calls for it. The list below is a cross-section of the work: offline-first data platforms, health monitoring tools, AI-assisted workflows, and developer utilities. Every item shipped through App Store review and is actively used.

Inventory and dispatch management platform for small businesses
Offline-first sync architectures with SwiftData and CloudKit
AI-powered meal planning and macro-tracking system
Apple Watch health and stress monitoring apps
Health data dashboards using Apple HealthKit
Xcode configuration diagnostic tooling for iOS developers

Who This Is For

I work with specific types of teams and projects. The best results come from clear fit. Most clients are building something that requires serious iOS engineering — not a website wrapped in a WebView, but a native app with local persistence, CloudKit sync, or on-device AI. If you are a funded startup, a privacy-first product team, or a team that has outgrown a fragile prototype and needs production-grade architecture, you are likely a good fit.

Ideal for
Funded startups building their first iOS app
Privacy-first products needing on-device processing
Complex data-driven apps requiring solid architecture
Teams needing production-grade architecture from day one
Not for
Marketing websites or simple content apps
Low-budget MVPs looking for the cheapest option
Template customization or white-label solutions
Projects requiring 24/7 support or immediate turnaround

Packaged Projects

Three predefined engagements, each with fixed scope, fixed price, and a defined deliverable. No hourly billing, no open-ended discovery phases, no scope creep. Each service covers a specific stage of iOS AI development: auditing an existing codebase, building a new app from scratch, or adding on-device AI intelligence to an existing product. If your project falls outside these, use the custom project form below.

iOS Architecture Audit

A structured 5-day async review of your iOS codebase covering MVVM/TCA pattern consistency, dependency injection, SwiftUI lifecycle issues, and Core ML readiness. Delivered as a prioritized roadmap with specific file-level recommendations. Teams typically surface 8–12 actionable architecture issues before their next App Store submission — reducing post-launch crash rates and compressing the next build cycle by weeks. The audit includes an on-device AI readiness assessment: whether your data model and inference pipeline are structured to support Core ML or Apple Foundation Models integration without a full rewrite.

Starting from

$1,500

5 days · Async-first, one live session

→ Prioritized technical roadmap

Start a Project

iOS MVP Sprint

A 4–5 week sprint delivering a SwiftUI codebase with local persistence, CloudKit or custom API sync, core screen navigation, and a TestFlight-ready binary. The sprint covers one primary data model end-to-end with production-grade architecture from day one — not a throwaway prototype. Fixed price from $9,000 with no hourly billing. Teams typically reach App Store submission within 4–8 weeks of sprint delivery. If your product requires iOS AI development features — on-device classification, smart suggestions, or local natural language processing — those can be scoped into the sprint from the start, so the AI layer is wired into the architecture rather than bolted on later.

Starting from

$9,000

4–5 weeks · Sprint-based, async collaboration

→ App Store-ready iOS/iPadOS app

Start a Project

On-Device AI Integration for iOS

A 3–4 week sprint integrating Core ML or Apple Foundation Models into an existing or new iOS app. Covers model selection, quantization, the Swift inference pipeline, and UI data binding. On-device inference delivers under 10ms response latency on A17 Pro and M-series chips, eliminates per-request API costs from third-party AI providers, and satisfies GDPR and CCPA requirements by keeping all user data on the device. On-device AI is the defining technical advantage for privacy-first iOS products in 2026: users get instant, offline-capable intelligence and your product earns their trust by never sending personal data to a remote server.

Starting from

$5,000

3–4 weeks · Focused integration sprint

→ Production AI feature, privacy-first

Start a Project

Proof

Real systems built through 3NSOFTS. Each case study follows the same structure: the problem the client faced, the architecture used to solve it, and the measurable outcome after launch. These are not wireframe demos or proof-of-concept projects — they are App Store products with real users. The on-device AI and CloudKit-backed apps in this section are particularly representative of the kind of iOS AI development work available through 3NSOFTS.

The Company App iPad screenshot showing inventory dashboard

The Company App

B2B Operations Platform · iOS & iPadOS

★★★★★5.0 · Live on App Store

Problem

Business owners running operations through messaging threads, paper trails, and approval bottlenecks. Decisions wait. Owners pay for tools their teams don't even own.

System

Owner-controlled CloudKit architecture. The owner holds the data and the subscription — team members join free under role-based permissions. Built on an ISO 27001-aligned operations model covering warehouse, sales, and dispatch.

Outcome

Approvals and team communication move from days to minutes. Paper-based bureaucracy disappears. The owner keeps control of every record on their private iCloud.

  • →One subscription covers the entire team
  • →Role-based access for warehouse, sales, dispatch, CRM
  • →Owner-owned data — never on a third-party server
  • →Notification-driven approvals replace email threads
Read case study →
BrieFolio document intelligence on iPhone, iPad, and Mac

BrieFolio

Document Intelligence · iPhone, iPad, Mac

★★★★★Free to start · App Store · New

Problem

You have a 40-page contract, a stack of meeting notes, or a research paper you don't have time for. Pasting them into ChatGPT means leaking your private documents to a third party. Reading them line-by-line means losing the day.

System

A smart extraction engine that works on any document, with purpose-built schemas for six common types. Powered by Apple's 3-billion-parameter on-device Foundation Models. Documents never leave the device.

Outcome

Drop in any document. Ask deeper questions. Get a layered summary instead of a one-paragraph skim. Compare two documents side-by-side. Without your data ever touching a server.

  • →Works on any document — specialized depth on 6 types
  • →Ask: conversational Q&A grounded in your document
  • →Deeper Summary: multi-level, not just one paragraph
  • →Foundation Models on-device — zero cloud, zero account
Learn more about BrieFolio →
ECHO Survival AI iOS app offline conversation screen

ECHO Survival AI

Offline AI Assistant · iOS · Free

★★★★★5.0 · Live on App Store

Problem

Most AI assistants stop working the moment your signal drops. In remote areas, on long flights, in places where connectivity is unreliable — the assistants people most need become useless.

System

A custom-tuned local model called Echo, downloaded once during install. Runs entirely on the device with no internet required afterward. Specialized for survival, first aid, water sourcing, shelter, and fire.

Outcome

A pocket assistant that works in the backcountry, on the plane, in the cabin, in any place a signal doesn't reach. Faster responses, better battery, and the only data leaving your device is the one-time model download.

  • →One-time install, then no internet ever
  • →Echo: custom local model, on-device inference
  • →Knowledge base tuned for survival and emergency use
  • →Works on every iPhone — performance scales with device
Learn more about ECHO Survival AI →
MovieArmyKnife — native macOS video toolkit screenshot

MovieArmyKnife

Native Video Toolkit · macOS · Free

18+ Tools · Free Forever

Problem

Every time you need to resize, compress, or trim a video on a Mac you end up in Terminal with FFmpeg, or downloading a sketchy Electron app with ads and watermarks. macOS has world-class media frameworks — but no utility that exposes them.

System

Pure SwiftUI app using AVFoundation and VideoToolbox exclusively. Non-destructive operation stack — Resize + Blur + Trim + Compress all compose into a single export pass. Real-time CoreImage filter preview during playback. Zero third-party dependencies.

Outcome

The video equivalent of Preview.app — lightweight, native, handles the 20 things you actually need daily. Hardware-accelerated H.265 export. 1-minute 4K clip in ~8 seconds on M2. Free forever, no IAP, no watermarks.

  • →18+ tools: resize, trim, merge, compress, convert, replace audio
  • →Hardware-accelerated H.264/H.265 via Apple Silicon media engines
  • →Zero network access — fully offline, sandboxed, no analytics
  • →Free forever — no subscription, no watermarks, no IAP
Read case study →

“3NSOFTS consolidated three disconnected tools into one iOS workflow and cut our coordination overhead by 65% in the first month.”

Daniel Rowe, Operations Director— Daniel Rowe, Operations Director

“Their architecture and tooling recommendations now save our team 4 to 6 engineering hours every time Xcode breaks a build pipeline.”

Mina Patel, Co-Founder— Mina Patel, Co-Founder

“The on-device AI architecture gave us 0-byte external data transfer and extended battery life by 40% for emergency use cases.”

Aisha Bennett, Product Lead— Aisha Bennett, Product Lead

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 run without a cloud connection.

Technical Writing · 73 Articles · Updated 2026

From the Lab

Production patterns, architectural trade-offs, and engineering analysis on iOS, on-device AI, and Apple platform craft. No tutorials.

Software Strategy9 min

iOS Development Company: How to Choose the Right Partner for Your Startup in 2026

A practical framework for choosing an iOS development partner in 2026, including partner types, pricing models, red flags, and the exact hiring questions founders should ask.

On-Device AI12 min

Apple Intelligence Integration: Complete Implementation Guide for iOS Apps in 2026

Implement Apple Intelligence in your iOS app using IntelligenceKit and FoundationModels. Covers text, vision, and audio APIs, privacy-first consent patterns, performance optimization, and App Store review requirements.

iOS Architecture10 min

iOS App Architecture Audit: 12 Critical Issues That Kill Production Apps in 2026

Most production iOS apps fail in the same places: weak architecture, main-thread work, brittle state, poor testing, compliance gaps, and no AI readiness. This guide shows the 12 issues to catch before they turn into crashes, delays, and rewrites.

Browse all 73 articles →

Unfair Advantage

Why teams choose 3NSOFTS when they need reliable systems, not quick demos. The four pillars below cover the areas that matter most for iOS products that need to survive past launch: offline reliability, on-device AI performance, a SwiftUI architecture that does not collapse under new features, and code that the next engineer on your team can actually read and extend.

Local-first architecture

Your app works even when signal drops. Data saves locally first, then syncs to iCloud in the background via CloudKit. For iOS AI development projects, local-first design means the inference pipeline and the data layer are always available — no waiting on a network round-trip before the model can run.

  • Built with Core Data and CloudKit.
  • Users can keep working offline.
  • Sync conflicts are planned early, not patched later.
  • Core Data + CloudKit sync reduces server API dependency by up to 80% for read-heavy workflows (Apple Developer Documentation, 2024).

On-device AI

We run AI on the device, not in the cloud. That keeps features fast, private, and free from per-request billing. On-device AI using Core ML or Apple Foundation Models runs at hardware speed on Apple Silicon — A17 Pro and M-series chips deliver under 10ms inference latency with no internet connection required. For startups building privacy-first products, on-device AI is the only approach that satisfies GDPR and CCPA by design.

SwiftUI systems design

We build SwiftUI code that scales beyond a prototype. Teams can add features without rewrites. The architecture follows a clear separation of data, business logic, and presentation layers — so integrating on-device AI features or new CloudKit-backed data models later is additive, not disruptive.

  • Clear data flow and modular screen structure.
  • Reusable components with predictable behavior.
  • Testing support for key screens and states.

Long-term maintainability

We optimize for the next 12 months, not only for launch week. That means architecture decisions are documented as they are made, dependencies are kept minimal, and every component is written to be readable by the next iOS developer who works on the codebase — whether that is an in-house hire six months from now or a second contractor extending your iOS AI features.

  • We document architecture decisions as we build.
  • Dependencies stay minimal and intentional.
  • Code stays readable for the next engineer on your team.

Shipped products

Built in production

Real apps on the App Store. Each one a working proof of a specific architectural decision.

The Company App app icon

The Company App

Offline-first business operations

Core Data + CloudKit sync

iOSiPadOS
Learn more →
ECHO Survival AI app icon

ECHO Survival AI

Fully offline AI assistant

Apple Intelligence · zero network calls

iOSOffline
Learn more →
Xcode Doctor app icon

Xcode Doctor

Xcode project diagnostics

Static analysis · no sandbox escape

macOSFree
Learn more →
See all 18 products →

Common Questions

Plain answers to the questions founders and product teams ask before starting.

What kind of apps does 3NSOFTS build?

Production-grade iOS, iPadOS, and macOS apps that ship to the App Store and are built to last. Most engagements involve complex data workflows: multi-role CloudKit sync, offline-first persistence with Core Data, or on-device AI with Core ML or Apple Foundation Models. Past projects include B2B operations platforms, document intelligence tools, offline AI assistants, and native macOS video toolkits. We do not take on simple CRUD apps, template customizations, or quick-turnaround prototypes that prioritize speed over architecture quality.

Do you work with idea-stage startups?

Yes — the iOS MVP Sprint is designed for idea-stage startups that have defined their product problem and are ready to build. We require the core use case, target user, and primary data model to be decided before the sprint begins. The sprint delivers a TestFlight-ready binary with production-grade SwiftUI architecture, local persistence, and sync — not a throwaway prototype. Teams typically move from sprint output to App Store submission within 4–8 weeks, with an architecture that supports new features without rewrites.

What is AI-native software?

AI-native software treats the inference pipeline as a first-class architectural layer, not a feature added after launch. In practice this means the model is wired directly into the data model, the UI responds to model outputs in real time, and the app degrades gracefully if inference is unavailable. We implement this using Core ML for custom models and Apple Foundation Models for natural language tasks. The result is AI behavior that is testable, versionable, and maintainable — not a black-box API call that breaks silently.

How long does a project take?

Each engagement has a fixed, published timeline. The Architecture Audit delivers a prioritized roadmap in 5 business days — fully async, with one optional live session at the end. The iOS MVP Sprint runs 4–5 weeks in focused two-week build cycles with weekly async progress updates. The On-Device AI Integration sprint runs 3–4 weeks depending on model complexity and existing codebase state. All three are fixed-scope and fixed-price with no hourly billing and no scope-creep surprises at the end.

What is on-device AI and why does it matter?

On-device AI means the inference model runs locally on the user’s iPhone or Mac — not on a cloud server. User data never leaves the device, which satisfies GDPR, CCPA, and Apple’s App Store privacy guidelines without additional compliance engineering. Apple’s Core ML framework delivers under 10ms inference latency on A17 Pro and M-series chips, making AI responses feel instant compared to round-trip cloud APIs. AI features work fully offline. There are zero per-request API costs from third-party AI providers, which eliminates a major cost driver as your user base grows.

Start a Project

New engagements start with a short application. It helps confirm we are the right fit before we begin.

Start a Project→View service offerings

Other inquiries

For partnerships, press, or non-project inquiries: info@3nsofts.com