AI inside
AI app development, features that earn their place.
Skyriven builds AI features into native iOS, macOS, and web apps: LLM features on the Claude, OpenAI, and Gemini APIs, and on-device intelligence where privacy or speed matter. Every feature ships with caching and cost controls, so a busy day never becomes a surprise bill. The studio is AI-native in how it works too: frontier coding tools write much of the code, and a senior human directs and reviews every change.
AI features we build
LLM features
Summarization, extraction, classification, and chat, built on the model that fits each job.
Vision and scanning
Camera features that read what users point at. Ask Nonna sends a photo of an ingredient label to Gemini, which transcribes it and returns a plain-English verdict.
On-device intelligence
Features that run on the phone with no server round trip. Saccade tracks where your eyes land in real time with ARKit face tracking, 100% on the device.
Search grounded in your data
Answers drawn from your own documents and records, not the open internet, with sources the user can check.
Cost and abuse controls
Caching, rate limits, and per-user budgets. Ask Nonna reserves a daily scan budget before every paid model call and serves repeat scans from cache.
Model choice, tested
We test Claude, OpenAI, Gemini, and on-device options on your real data for quality, speed, and cost per request before recommending one.
AI features shipped from the studio
Before we build yours, we build ours. Every app here was designed and built in-house.
Ask Nonna
Social · Food · Apr 2026
Scan any packaged product and Nonna tells you whether the ingredients are normal and unprocessed. A food social movement built around one simple question.
Saccade
A/B Testing · Mar 2026
A/B testing with your eyes. Upload image variants and Saccade uses real-time gaze tracking to rank which ones you naturally look at longer. 100% on-device, no account needed.
Pricing
Fixed scope, no hourly billing. Every project starts with a free 20-minute call and an exact proposal. We take on one build at a time, so yours gets the whole studio.
Prototype Sprint
3 to 4 weeksfrom $10,000
A working prototype on iPhone, Mac, or the web. Real, not a clickable mockup.
- Product and UX scoping session
- One platform: native SwiftUI or modern web
- Weekly builds on TestFlight or a preview URL
- Full source code and handoff walkthrough
50% to start, 50% on delivery
Start a sprintLaunch Build
Typically 6 to 10 weeksfrom $35,000
Your v1, designed, built, tested, and shipped to the App Store, Mac App Store, or the web.
- Product design and interface system
- Production-grade native or web engineering, one platform
- AI features where they earn their place
- QA, analytics, and crash reporting
40% to start, 30% at first beta, 30% at submission
Plan a launchStudio Partner
Month to monthfrom $7,500 /mo
An embedded product studio after launch. One feature in flight at a time, a release every two weeks.
- Continuous feature development, one workstream at a time
- A release every two weeks
- OS-update readiness, maintenance, and fixes
- Product and roadmap sessions
Billed monthly in advance
Become a partnerVenture-backed? You can pay up to half of a project fee in equity. How it works
Questions about AI App Development
How much does it cost to add AI to an app?
Most AI features start with a Prototype Sprint (from $10,000, 3 to 4 weeks) that proves the feature on your real data, then ship in a Launch Build (from $35,000) or through Studio Partner (from $7,500/mo) for an app that is already live. Model usage fees from Claude, OpenAI, or Gemini are billed to your own API accounts.
Which AI model should my app use?
It depends on the feature. We test candidates from Claude, OpenAI, Gemini, and Apple's on-device frameworks against your real data for quality, speed, and cost per request, then recommend one. Many apps end up using more than one model.
Can AI features run on-device instead of in the cloud?
Often, yes. Apple's on-device frameworks handle vision, face and gaze tracking, text recognition, and smaller language tasks with no data leaving the device. Saccade's gaze tracking runs entirely on the iPhone. Larger reasoning tasks still need a cloud model.
How do you keep AI API costs under control?
With caching, rate limits, per-user budgets, and the smallest model that does the job well. Ask Nonna, for example, serves repeat scans from cache and reserves a daily budget before every paid Gemini call, so costs scale with real use rather than with abuse.
Do you build AI chatbots and assistants?
Yes, when one fits the product. We build in-app assistants grounded in your own content, with clear limits on what they can do and a way to reach a human. If a simpler feature like search or summarization would serve your users better, we will say so.
More from the studio
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