Opportunities › Local AI models on mobile devices › Proposed app
Stillwire
Run open AI models on your Android phone. No root, no cloud, no setup.
- Score
- 32
- confidence 36
- Evidence
- 3
- items on the page
- Rivals
- 0
- named in sources
- First version
- 40 d
- estimate
- Type
- Mobile app
- PWA: installs on iPhone and Android
- Market since
- 2023
- Emerging market · AI estimate
ScreensConcept
Mobile app: Users run AI models on Android phones and tablets for offline chat and file Q&A, with quick access to local models without cloud dependency or setup. Sample screens on a phone, in the proposed brand. Their numbers are sample data.
Device check
6 GB free
- Memory available6.2 GB
- Storage free48 GB
- GPU accelerationSupported
- Small modelsSmooth
- Mid-size modelsSlow
About this appAI proposal
Stillwire is a private AI workbench that installs from the browser and runs open language models on your own Android phone or tablet. Pick a model, download it once, and chat, summarise files or run small agents with no account and no connection needed.
It is built for people who want local AI without rooting a device or piecing together a terminal, a runtime and a file manager by hand. Models, chats and files sit in one app. A single storage screen shows what each model costs in space and memory.
Different from the DIY route: nothing to compile, no separate tools to install. Different from cloud assistants: prompts stay on the device unless you choose to send a job to the optional cloud tier. Speed depends on your phone, and the app tells you before you download.
- Tagline
- Your AI, on your phone, and nowhere else.
- Voice
- CalmPlainPrivatePractical
- Why this name
- Still means quiet and unmoving. Wire hints at the connection you no longer need. Together: AI that works with the line cut. Trademark check needed.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
Device check before download
Tests memory, storage and GPU support, then lists only the models your phone can run well.
No member yet
One-tap model library
Browse open models in small sizes, download them once and keep them on the device.
No member yet
Offline chat and file Q&A
Ask questions about PDFs and notes stored on the phone. Nothing leaves the device.
No member yet
Built-in workbench
Sandboxed terminal-style console, file manager and reader in the same app, so no extra installs.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#1F5C4DPine · primary#F4EFE6Oat · surface#1B2724Charcoal Green · text#E0833AEmber · accent#4C7F86Slate Teal · data
Typography
Aa
Stillwire
ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
Your AI, on your phone, and nowhere else.
PricingAI proposal
The material gives no competitor prices. These tiers are a starting point to test, following the monetization idea in the opportunity: freemium, model packs and a cloud tier.
Free
Free
- Device check
- Small model library
- Offline chat
- Local file Q&A
Pro
$6 a month
- Larger model packs
- Local agents with logs
- Encrypted cloud backup
- Storage and battery limits
Developer
$15 a month
- Local JavaScript endpoint
- Cloud fallback credits
- Priority model updates
Would you pay Pro · $6 a month?
Your answer tells PWAS which prices people accept. It changes no score.
No answers yet.
What it could be worthEstimate
What a software business making this much sells for today, from real deals. Pick a monthly revenue.
If it makes
Worth about
$190,000
Sale range $132,000 to $263,000
$120,000 a year in revenue
From 87 software businesses listed and sold on Empire Flippers in the last year, revenue vetted by the broker: they sell for about 19× their monthly revenue, most between 13× and 26×.
Measured on profit, the middle deal is 32× monthly net profit: about 2.7 years of profit.
An estimate, not an offer or financial advice. A real price depends on profit, growth, churn, how much of the work is the owner's, and the buyer.
How it would growAI proposal
How the product would reach new customers through its own use, and how the first ones would be found. A plan to test, not a result.
- Built-in loop
- No loop in the product. Reaches customers through content, developer communities and search. Local use leaves no shared output, so no built-in loop exists; the local endpoint may later show the app name to a developer's own users.
- Do they become customers?
- Test whether free users on capable phones convert to Pro for larger packs and backup, and whether developers pay for the endpoint. Both are unproven.
- First customers
- Privacy-minded Android power users and indie mobile developers who already try local models and want them to work without root or Termux.
- Where to reach them
- Developer forums and GitHub: Post a working demo and a device compatibility list where local-AI projects are discussed.
- Android and privacy communities: Share short offline-mode videos on Reddit and in privacy groups, linked to a free waitlist.
- First milestone
- 500 waitlist sign-ups and 15 paying Pro users from Android power users within 60 days of launch.
Why people already pay for this
- VerifiedGitHub repository gained 347 stars in 73 days
- Public claimDSHBox integrates and coordinates multiple systems to enable running DeepSeek Harness locally on Android without root access.
- AI inferenceThe project has attracted developer interest with 347 stars and 19 forks on GitHub, indicating market validation for local AI on mobile.
Tech stack
Every proposal builds on the same PWA base, installable from the browser on any phone or computer. Dashed boxes are what this app adds.
- AppNext.js and TypeScript
- PWAManifest and service worker
- UITailwind CSS
- Data and authSupabase Postgres
- PaymentsStripe
- EmailResend
- HostingVercel
- This app · On-device inferenceWebGPU and WebAssembly LLM runtimeRuns quantized open models inside the browser on unrooted Android with no native install.
- This app · Model storageOrigin private file system plus resumable downloadsMulti-gigabyte model files must be stored on the device and survive interrupted downloads.
RisksAI inference
- TechnicalBrowser-based inference is slower and more memory-limited than native apps. Many phones may only manage small models, which could disappoint users expecting DeepSeek-class quality.
- PlatformAndroid browsers differ in WebGPU support, storage limits and background throttling. A PWA may be evicted or paused during long runs and agent tasks.
- CommercialEvidence is GitHub interest only (347 stars in 73 days). Developers starring a repo may not pay, and free local apps already exist.
- Intellectual propertyEach model has its own licence terms. Redistributing files or charging for model packs needs checking per model.
- AISmall local models make more mistakes. Agents that act on files need strict permissions to avoid unwanted changes.
Everything marked AI proposal or AI inference was written by a model from the evidence on the opportunity page. The proposed name must be checked against trademark registers before it is used.