Feature spec
Goal: Send a clear invoice after finishing a job.
- Add a client, line items, a due date, and payment instructions.
- Preview the total before exporting a PDF.
- Keep an editable draft if export fails.
App Overview
Local LLM: Private Secure Chat
Pay once
$9.99 · In-app purchases
PRICE
$9.99
In-app purchases
BUSINESS MODEL
Paid
No overall Grossing estimate available
RATING
★ 3.0
4 ratings · Below Average
Evidence scope: No current overall US chart position is available. Category-chart positions shown in discovery are a separate scope. Revenue is a directional model estimate, not verified earnings.
Build your own version
Build Kit
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A product spec, screen plans, and build steps for your coding agent.
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What's included18 files
A product spec, phased build plan, differentiation notes, and screen references.
- START_HERE
- AGENTS
- EVIDENCE
- SPEC
- BUILD_PLAN
- DIFFERENTIATION
- skills/
- screens/
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Illustrative example: an invoice app for independent contractors. Your kit is tailored to the app you choose; this is not its generated content.
Screen plan
Invoice editor: Client at the top, editable line items in the middle, total and preview action at the bottom.
States: Empty draft, validation errors beside each field, exporting, and a retry action that preserves the draft.
Differentiate and validate
Hypothesis: Contractors need faster repeat invoices more than more templates.
First experiment: Test duplicating a previous job with five contractors. Watch where they hesitate before expanding the feature set.
The full kit adds a phased build plan, evidence notes, tool prompts, and implementation guidance. It is a plan for your coding agent, not a finished app.
Usage: Mechanics are fair game; never reuse the original name, branding, assets, or verbatim copy.
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Free quick prompt For a smaller starting point
Quick prompt
Good fit for mobile-first iOS and Android prototypes with managed app scaffolding.
// RORK SYSTEM PROMPT
Rork plan preview for Local LLM: Private Secure Chat: map the core Utilities workflow, choose the smallest differentiated feature set, define the data and monetization boundaries, then prototype the riskiest user journey first.
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Opportunities
AI-GENERATED OPPORTUNITY HYPOTHESES
These are generated suggestions, not verified review quotations. Check current App Store reviews and speak with users before treating a possible gap as a requirement.
Hypothesis 1
Implement group chat features to enhance user experience.
Assumption to check: Limited functionality for group chats
Validate with people who use this workflow before building.
Hypothesis 2
Focus on improving user feedback and fixing bugs.
Assumption to check: 3.4/5 rating indicates user dissatisfaction
Validate with people who use this workflow before building.
Hypothesis 3
Allow users to customize themes and chat backgrounds.
Assumption to check: No customization options for chat interface
Validate with people who use this workflow before building.
Hypothesis 4
Introduce image and file sharing features.
Assumption to check: Lack of media sharing capabilities
Validate with people who use this workflow before building.
App evidence
Original App Store material. Ratings and screenshots describe the existing app, not proof of demand for your version.
App Store description
Pay once. Use forever. No subscription. No cloud. No data collected. Local LLM is the most private AI assistant on iOS. Everything runs 100% on your device. Your prompts, chats, and data never leave your iPhone, iPad, or Mac. One-time purchase. Lifetime updates. Family Sharing included. ≈ WHY LOCAL LLM ≈ ◉ Zero Subscriptions One purchase. No account. No API keys. No monthly fees. Ever. ◉ 100% Offline and Private No internet required. Nothing stored, tracked, or transmitted. Perfect for healthcare, legal, finance, or anyone handling sensitive work. ◉ No Filters. No Restrictions. Run uncensored open-source models. Ask anything. Get real answers. ◉ Leading Open-Source Models Optimized for Apple - LLaMA (Meta): strong general-purpose reasoning - Mistral: fast, compact, great for logic - Phi (Microsoft): lightweight everyday assistant - DeepSeek: tuned for math and code - Qwen (Alibaba): multilingual strength - Gemma (Google): safe, helpful responses ◉ Built for Apple Silicon Native Swift and Metal. Fast inference. Full Siri and Shortcuts integration. ≈ USE IT FOR ≈ ◎ Drafting docs and emails with zero leakage risk ◎ Reviewing confidential or proprietary content securely ◎ Writing and testing code with no cloud exposure ◎ Getting unfiltered answers to anything ◎ Staying productive offline or without Wi-Fi Local LLM is built by Pocket Bits LLC, a USA-based, OPSWAT Anti-Malware Certified developer. Questions or feedback? [email protected]
Written user reviews are not shown here. Check current App Store reviews >
Screenshots
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Build scope
Plan a focused first version with your coding agent. These are planning assumptions, not a delivery guarantee.
Define the first version
Choose one audience and one core workflow. Use the kit to agree on its screens, data, and acceptance criteria before building.
Set boundaries
Decide which secondary features, integrations, and platform support can wait. Your version does not need to reproduce everything in the original.
Check the hard parts
Validate external services, specialist technology, data access, and ongoing costs for your chosen scope.
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BUILD KIT DIFFICULTY
Advanced
From the Build Kit assessment.
A reliable timeline needs an agreed scope and a technical check. Ask your agent to estimate the phases in BUILD_PLAN.md after that review.
