OpenIntelligence - Sell Project
Project Overview
OpenIntelligenceOpenIntelligence is a private Apple-native document-intelligence engine that currently lives inside a shipped iOS codebase.The public app is the proving ground. The thing for sale is the engine itself: the Swift/iOS code, the current source-distributed SDK lane, the evaluation materials, and the handoff context around it.This started because I kept wanting AI help with the exact documents I did not want pushed through a generic hosted workflow. Manuals. IFUs. Service guides. Inte...
Detailed Description
Visual Content & Media
Project Screenshots & Interface
The following screenshots showcase the visual design and user interface of OpenIntelligence:
Screenshot 1: Main Dashboard & Primary Interface
This screenshot displays the main dashboard and primary user interface of the application, showing the overall layout, navigation elements, and core functionality. The interface demonstrates the modern design principles and user experience patterns implemented using Swift,JavaScript,CSS,Shell,Ruby,Python,HTML.
Screenshot 2: Key Features & Functionality
This screenshot displays key features and functionality of the application, demonstrating specific capabilities and user interactions. The interface demonstrates the modern design principles and user experience patterns implemented using Swift,JavaScript,CSS,Shell,Ruby,Python,HTML.
Project Demonstration Videos
The following videos provide visual demonstrations of OpenIntelligence in action:
Demo Video 1: Main Functionality Walkthrough
This video demonstrates the main functionality and core features of the application, providing a comprehensive overview of how the system works. The video showcases the mobile application's technical implementation using Swift,JavaScript,CSS,Shell,Ruby,Python,HTML and user interface design, providing viewers with a clear understanding of the project's capabilities and value proposition.
Video URL: https://www.loom.com/share/9860865ae137493bb87ebf7fa44ce28e
Live Demo & Interactive Experience
Live Demo URL: https://github.com/Gunnarguy/OpenIntelligence
Experience OpenIntelligence firsthand through the live demo. This interactive demonstration allows you to explore the application's features, test its functionality, and understand its user experience. The live demo showcases the mobile application's technical capabilities implemented with Swift,JavaScript,CSS,Shell,Ruby,Python,HTML and real-world performance, providing a comprehensive understanding of the project's value and potential.
Visual Content Summary
This project includes 2 screenshots and 1 demonstration video plus a live demo, providing comprehensive visual documentation of the mobile application. The media content demonstrates the project's technical implementation using Swift,JavaScript,CSS,Shell,Ruby,Python,HTML and user interface design, showcasing both the visual appeal and functional capabilities of the solution.
Technical Specifications & Architecture
Technology Stack & Implementation
Primary Technologies: Swift,JavaScript,CSS,Shell,Ruby,Python,HTML
Technology Count: 7 different technologies integrated
Implementation Complexity: High - Multi-technology stack requiring extensive integration expertise
Technology Analysis
Common Questions & Use Cases
Use Cases & Practical Applications
Target Audience & Use Cases
Business Use Cases: This project is ideal for businesses looking to implement a ready-made solution. Perfect for entrepreneurs, startups, or established companies seeking mobile solutions.
Project Details
Project Type: Mobile
Listing Type: Sell
Technology Stack: Swift,JavaScript,CSS,Shell,Ruby,Python,HTML
What's Included
Source code, All related design work
Included in the sale or license discussion by default: Private engine/source-code repo snapshot or agreed repo transfer scope pinned to a commit Repo-root Swift package surface for OpenIntelligenceEngine Current public engine facade under OpenIntelligence/SDK/OpenIntelligenceEngine.swift Engine-relevant Swift source across document processing, chunking, embeddings, storage, vector search, retrieval, verification, and answer orchestration layers Repo-side source consumer sample app and simulator smoke-test path Buyer packet zip Partner packet zip Packet-local evaluation host app Benchmark harness code, reporting scripts, and evaluation fixtures already in the repo Limited handoff documentation Limited post-transfer clarification if written into scope Incidental repo context only, not part of the asset story: Some app-side project files remain in the same repo because the engine currently lives inside that tree. Default handoff path: Scope and exclusions are written down. The buyer packet and partner packet are used for diligence. The transfer is pinned to a named commit SHA. Delivery happens via repo transfer or repo archive plus both packet zips. A short handoff call is held. The buyer confirms receipt of access and artifacts. Not included by default: App Store app transfer App Store listing or release pipeline consumer app business context Apple Developer account access signing certificates provisioning profiles API keys or service credentials personal accounts private benchmark corpora sensitive benchmark traces long-term support custom feature development exclusivity production SDK warranty regulated-use validation Separately negotiable: App Store app transfer exclusive field-of-use license broader source-code acquisition longer transition support custom integration help private walkthrough sessions deeper SDK cleanup and packaging work
Reason for Selling
I feel that the project requires skills that I do not necessarily have and would like to see someone else take over.
Technical Architecture
Technology Stack & Architecture
This mobile project is built using a modern technology stack consisting of Swift,JavaScript,CSS,Shell,Ruby,Python,HTML.
Architecture Type: Mobile - This indicates the project follows mobile-first design principles with responsive interfaces.
Technical Complexity: Multi-technology stack requiring integration expertise
Business Context & Market Position
Development Context & Timeline
Project Development Timeline
This project was created on May 3, 2026 and last updated on September 13, 2026. The project has been in development for approximately 4.4 months, representing 133.13103249601 days of development time.
Development Commitment: The project requires 20-40 hours/week of development time, indicating a part-time level commitment.
Technical Implementation Effort
Implementation Complexity: High - The project uses 7 different technologies (Swift,JavaScript,CSS,Shell,Ruby,Python,HTML), requiring extensive integration work and cross-technology expertise.
Next Development Phase: <p>If I were buying this from someone else, I would think about it as a head start, not a finish line.</p><p><br></p><p>First thing I’d suggest is looking into Apple’s LoRA - seems remarkable and I don’t have the hardware to make it possible.</p><p><br></p><p>The most obvious next move is engine separation. The valuable logic already exists, but parts of it are still coupled to app services, runtime paths, storage assumptions, diagnostics, and UI surfaces. A buyer could turn that into a cleaner SDK or internal framework with a narrower API and a more reproducible handoff path.</p><p><br></p><p>After that, I think the biggest gains are in retrieval and source fidelity. The engine already has ingestion, OCR-oriented processing, chunking, local full-text search, vector retrieval, context packing, Apple Foundation Models integration, source review, verification-oriented behavior, and benchmark tooling. What still needs work is getting the exact right supporting chunk or page more reliably, preserving important evidence through packing, and getting the system better at refusing when support is weak.</p><p><br></p><p>The other big area is hard documents. Manuals, IFUs, service guides, spec-heavy PDFs, tables, and procedural material are exactly why I built this, and they are also the hardest things to get right. That means table extraction, page-level evidence, procedural-step fidelity, cross-reference handling, and exact-value lookup are all good places for a buyer to keep pushing.</p><p><br></p><p>I also think the benchmark side matters more than the demo side. The benchmark harness gives a buyer a way to test the engine on their own corpus instead of just watching me run a polished sample. For the right buyer, that is where the real value starts showing up. It would need fine-tuning for whichever domain the buyer intends to aim it towards.</p><p><br></p><p>The strongest buyer path is probably not trying to make this work for every document on earth. It is to narrow it around one real workflow where grounded answers over private docs are actually worth money.</p><p><br></p><ol><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Field-service manuals</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Internal technical references</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>compliance material</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Product support libraries</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Training workflows</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Private knowledge bases on Apple devices</li></ol><p><br></p><p>That is the opportunity as I see it: take the real ingestion, indexing, retrieval, context prep, answer generation, source review, and benchmark work that already exists here, then harden it around one actual buyer problem until it becomes much more than a prototype.</p>
Competitive Analysis & Market Position
Market Differentiation
Technology Advantage: This project leverages Swift,JavaScript,CSS,Shell,Ruby,Python,HTML to create a unique solution in the mobile space. The technology stack provides cutting-edge technical implementation that sets it apart from traditional solutions.
Competitive Advantages
- Modern Technology Stack: Swift,JavaScript,CSS,Shell,Ruby,Python,HTML provides scalability, maintainability, and future-proofing
Pricing Information
Offer Price: $3,000 USD
Project Metrics
Average Monthly Visitors: Undisclosed
Average Monthly Revenue: Undisclosed
Average Monthly Downloads: Undisclosed
About the Creator
Developer: User ID 229564
Project Links
Key Features
- Built with modern technologies: Swift,JavaScript,CSS,Shell,Ruby,Python,HTML
- Listed for sale
Frequently Asked Questions
What is this project about?
OpenIntelligence is a mobile project that OpenIntelligenceOpenIntelligence is a private Apple-native document-intelligence engine that currently lives inside a shipped iOS codebase.The public app is the proving ground. The thing for sale is t....
How much does this project cost?
This project is listed for sale at $minimum USD. There's also an offer price of $3,000 USD.
What's included when I buy this project?
Source code, All related design work.
Why is the owner selling this project?
I feel that the project requires skills that I do not necessarily have and would like to see someone else take over.
What technologies does this project use?
This project is built with Swift,JavaScript,CSS,Shell,Ruby,Python,HTML. These technologies were chosen for their suitability to the project's requirements and the developer's expertise.
What are the project's current metrics?
Monthly visitors: Undisclosed. Monthly revenue: Undisclosed.
Can I see a live demo of this project?
Yes! You can view the live demo at https://github.com/Gunnarguy/OpenIntelligence. This will give you a better understanding of the project's functionality and user experience.
How do I contact the project owner?
You can contact the project owner through SideProjectors' messaging system. Click the "Contact" button on the project page to start a conversation about this project.
Is this project still actively maintained?
Since this project is for sale, the current owner may be looking to transfer maintenance responsibilities to the buyer.