hasaneyldrm/ailandscape.org — explained in plain English
Analysis updated 2026-08-02 · repo last pushed 2026-03-19
Find open-weights models by filtering tags to see what already exists before building a product.
Map out which companies build infrastructure versus consumer products for recruiting or investment research.
Browse and discover AI tools across categories like security and research labs on a single organized page.
Share a specific filtered view of the AI landscape with a teammate by copying the web address.
| hasaneyldrm/ailandscape.org | 00kaku/gallery-slider-block | 04amanrajj/netwatch | |
|---|---|---|---|
| Stars | — | — | 0 |
| Language | — | JavaScript | Rust |
| Last pushed | 2026-03-19 | 2021-05-19 | — |
| Maintenance | Maintained | Dormant | — |
| Setup difficulty | easy | easy | moderate |
| Complexity | 1/5 | 2/5 | 3/5 |
| Audience | pm founder | general | ops devops |
Figures from each repo's GitHub metadata at analysis time.
No special infrastructure or API keys needed, the tool catalog data lives in simple text files.
ailandscape.org is an interactive map of the AI tools ecosystem. Think of it as a visual directory that helps you make sense of the crowded and fast-moving world of artificial intelligence. Instead of scrolling through scattered blog posts or spreadsheets to find the right tool, you get a single organized page where you can browse hundreds of AI tools sorted into categories like models, infrastructure, security, and research labs. The project works like a specialized website with a built-in catalog. You can search for specific tools by name, click on tags to filter everything by technology type, or expand and collapse categories to focus on what matters to you. Every action you take, like applying a filter, updates the web address, so you can bookmark your view or share it with someone else. It also includes a command palette (triggered with Command+K) for quick keyboard-driven searching, supports dark mode, and is built to be accessible to people using screen readers. This would be useful for founders, product managers, or investors who need to understand the competitive landscape before building or funding something. For example, if you are starting a company and want to see what open-weights models already exist, you could filter by the relevant tag and immediately see options like Nous Research alongside their descriptions and links. A technical recruiter could also use it to map out which companies are building infrastructure versus consumer products. What is notable about how it is built is where the data lives. Instead of locking the tool list in a complex database, every tool and category is stored in simple text files. This means anyone can propose adding a new tool just by editing a text file and submitting it, no database wrangling required. It is a practical approach that keeps the project maintainable and encourages community contributions.
An interactive visual map of the AI tools ecosystem that lets you browse, search, and filter hundreds of AI products sorted into categories like models, infrastructure, and security.
Maintained — commit in last 6 months (last push 2026-03-19).
No license information is provided, so default copyright restrictions apply.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly pm founder.
This repo across BitVibe Labs
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