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Cycls1 streamlines AI application development by generating apps from high-level descriptions. It eliminates boilerplate, ensures cross-platform compatibility, and manages memory - all from a single codebase.
With Cycls, you can quickly prototype ideas and then turn them into production apps, while focusing on AI logic and user interactions rather than wrestling with implementation details.
✨ Core Features
Fast App Generation: Create live web apps from code in minutes
Built-in Memory Management: Integrated state and session management
Rich Hypermedia Content: Support for various media types (text, images, audio, video, interactive elements)
Framework Agnostic: Compatible with a wide range of AI frameworks and models
Define the company/business in a single declarative sentence
Cycls is an AI platform that generates and launches AI applications for businesses and developers.
2. Problem
Describe the pain of the customer (or the customer’s customer)
AI application development is moving so fast that businesses struggle to keep up and use it effectively
Businesses struggle to quickly turn AI concepts into functional applications
Scaling AI solutions across different platforms is challenging and time-consuming
Outline how the customer addresses the issue today
Hiring AI specialists or outsourcing, leading to high costs and loss of control
Using limited, pre-built AI tools that lack customization and flexibility
Spending months on development and testing, delaying time-to-market for AI-powered innovations
3. Solution
Demonstrate your company’s value proposition to make the customer’s life better
Cycls is an AI platform that simplifies the entire lifecycle of AI application development. Our streaming architecture accelerates how businesses and developers launch and scale powerful AI solutions.
Show where your product physically sits
Cycls sits at the top of the AI application layer as part of the AI native stack, alongside other emerging technologies
(table to visual needed)
Layer
Components
Description
User Interface
-
The top layer where users interact with AI applications
2022-Present (Post ChatGPT launch): Explosive growth in AI capabilities and business interest
Define recent trends that make your solution possible
Key Trends Enabling Cycls:
Maturation of Large Language Models (LLMs)
Increasing demand for AI across industries
Rise of AI-assisted development
5. Market Size
Identify/profile the customer you cater to
Businesses:
Medium to large enterprises across various industries looking to integrate AI into their operations
Tech-forward companies seeking to rapidly prototype and deploy AI solutions
Organizations with existing development teams looking to accelerate AI adoption
Developers:
Individual developers and small teams interested in building AI-powered applications
AI researchers and data scientists needing tools for quick experimentation
Startup founders looking to incorporate AI into their products
Calculate the TAM (top down)
TAM (Total Addressable Market) - Top Down Approach
According to IDC, spending on GenAI solutions is projected to reach $151.1 billion by 2027, with a compound annual growth rate (CAGR) of 86.1% over the 2023-2027 forecast period5.
SAM (bottoms up)
SAM (Serviceable Addressable Market) - Bottom Up Approach
Enterprises adopting AI:
Estimated 70,000 medium to large enterprises globally
Average annual AI software spend: $10,000
SAM from enterprises: 70,000 * $10,000 = $700 million
Individual developers and small teams:
Estimated 1 million developers interested in AI
Average annual spend on AI tools: $360
SAM from developers: 1,000,000 * $360 = $360 million
Total SAM = $700 million + $360 million = $1.06 billion
This market size analysis demonstrates the significant potential for Cycls in the growing AI software market, with a realistic initial target of $21.2 million in annual revenue within the first 3-5 years of operation.
6. Competition
List competitors
We could make a point here that competition is commming from both big players (openAI) and small players frameworks (Streamlit/Gradio)
List competitive advantages
Consider chainlit at least internally (becoming closed source, what are their mistakes?)
What about HuggingFace spaces, could we make an arguemnt that they're dist for Gradio? would be nice if there is a big number to go along with it.
مبادرة الذكاء الاصطناعي لخدمة المعرفة الإسلامية والعربية
نبذة عن الشركة
سايكلز هي شركة تقنية تأسست في الرياض عام 2021 على يد نخبة من مهندسي الذكاء الاصطناعي وخبراء البيانات.
تتمثل رسالتنا في إحداث تحول جذري في كيفية إدارة المؤسسات للمعرفة ونشرها واكتشافها باستخدام تقنيات الذكاء الاصطناعي.
نسعى جاهدين لتسخير أحدث ما توصلت إليه التكنولوجيا لفتح آفاق جديدة في عالم إدارة المعرفة، مستندين إلى خبراتنا العميقة في مجال الذكاء الاصطناعي وتحليل البيانات. نطمح من خلال جهودنا إلى تمكين المؤسسات من الارتقاء بقدراتها المعرفية وتحقيق أقصى استفادة من مواردها الفكرية بطرق مبتكرة وفعالة.
نبذة عن المبادرة
أسست شركة سايكلز للتقنية بالرياض عام 20٢١م، وتختص بتقديم الخدمات التقنية المتعلقة بالذكاء الاصطناعي بشتى المجالات كالقطاع الصحي، والمالي، والإسلامي
## Private Roadmap
- Messaging Apps Support (e.g. WhatsApp, Telegram, Discord, Slack)
- Multimedia Input: Voice, File, and Image...etc
- Super app/chat as agent
- Mobile SDKs
- Monitoring
---
> Cycls: B2B SaaS platform for businesses and developers to create, launch, and manage AI applications
## Go to market strategy?
Developers
UI, Cross-platfrom/One-codebase, other cross ==> Network
Businesses
Use-cases? website?
## The crosses
(distribution network)
double address + triple reach
# Vision
From generator to generated
## Why now?
> First a node generation argument then an edage one
Our applications often exist in silos, isolated from one another, and require substantial effort to work together. This isolation prevents apps from maximizing their collective potential. As a result, **developers** are constantly incentivized to reinvent the wheel, wasting valuable time and effort.
However, recent progress in generative AI is allowing programs to interact using natural language. This means that both **users** and **systems** can now communicate and understand each other under a unified interaction model.
Cycls is building a network based on this dialogue-based interaction model. Developers can quickly launch user-ready apps that are designed to naturally integrate with any other AI app on the network.
By simplifying the process of creating and integrating applications, developers can focus more on their own unique problems. This streamlined developer experience translates to better apps for users.
## How does Cycls work?
Cycls offers a simple SDK that turns your application into a **node on the network**, Here's how it works:
As a developer, you start by choosing a unique name for your app, similar to selecting a Twitter/X handle. This becomes your app's global identifier on the Cycls network (e.g., `@app-name`).
The SDK turns your app into an HTTP server and registers its address with the network. The process is designed to be straightforward and requires minimal changes to your existing code.
When a user visits your app's page at `cycls.com/@app-name` and messages it, Cycls sends a notification to your server.
Your app then streams data back to Cycls, which it relays in real-time to the user's browser.
This **streaming architecture** ensures a seamless flow of information between your app and the user, with Cycls acting as the router.
All responses are in hypertext. This format works well with AI models and can be easily turned into rich, interactive content for users. It helps AI apps communicate naturally and gives users an engaging experience.
A key benefit of the **streaming architecture** is that your apps run on your own servers. This means you keep full control over your data and how your app operates.
Cycls uses standard web technologies, making it easy to scale your app. As your user base grows, you can handle increased demand without major changes.
# Goal?
> Node / Edge + easier read
At **Cycls**, our mission is to build the **AI native network** where apps can work together with agency, maximizing their **collective potential**.
