# TrajectoryRL - **Website:** - **Primary alias:** `trajrl.com` ## Description TrajectoryRL is an open AI research lab focused on building capable agents using small, open models. The project operates within Bittensor Subnet 11, where its work is vetted through continuous open competition. This emphasis on ongoing evaluation gives visitors a way to follow results as they emerge rather than relying only on static claims about agent performance. The TrajectoryRL website provides access to live activity, winners, a leaderboard, benchmark information, and documentation. These resources help users explore competition outcomes, compare participating agents, and learn more about the project’s approach. The site also links to the lab’s GitHub and X/Twitter accounts for further updates and materials. TrajectoryRL presents itself as an open-minded research effort, combining agent development with a public competitive setting. Its central offering is research and evaluation around agents built on small open models, supported by tools and information for tracking performance across the subnet. The available site text does not specify commercial products, paid services, or particular model capabilities, so its focus is best described as open AI research and competition. ## Industries - 🖥 Computers Electronics and Technology - 🖥 Artificial Intelligence and Machine Learning _(under Computers Electronics and Technology)_ ## Links - [twitter](https://twitter.com/TrajectoryRL) - [github](https://github.com/trajectoryRL) ## Logos & icons - logo _(primary)_ — PNG — [download](https://cdn.brandfetch.io/idD3agqwaO/w/64/h/57/theme/dark/logo.png?c=1bxid64Mup7aczewSAYMX&t=1791349133167) - icon _(primary)_ — JPEG — [download](https://cdn.brandfetch.io/idD3agqwaO/w/400/h/400/theme/dark/icon.jpeg?c=1bxid64Mup7aczewSAYMX&t=1791349133363) ## Colors | Name | Hex | Theme | | --- | --- | --- | | Shark | #1a1a1e | dark | | Pampas | #f5f4ee | light | ## Fonts - var(--font-mono) — asset _(custom)_ --- _Source: _ _See [/llms.txt](/llms.txt) for a full list of agent-readable pages, and [/auth.md](/auth.md) for how agents authenticate._