BitFan
Public Service Atlas for Bittensor
BitFan
MANTIS lets technical users build and test short-horizon financial forecasting signals, but it does not yet offer a polished public app, packaged signal feed, or self-serve consumer API.
MANTIS is a technical market-forecasting research system. It is designed to compare forecasting models across multiple asset classes and market tasks. In plain English, it gives technical contributors a structured environment for producing and testing market signals. The target user is not a casual trader. It is a quantitative developer, machine-learning researcher, or technical market-signal builder who can run Python tools, obtain market data, and understand backtesting. What is usable today is the open-source developer workflow: the main repository, technical docs, and local model-iteration tool. What is not usable today is a polished public app, paid signal feed, consumer dashboard, hosted API, or no-code demo.
The target user is not a casual trader. It is a quantitative developer, machine-learning researcher, or technical market-signal builder who can run Python tools, obtain market data, and understand backtesting.
What is usable today is the open-source developer workflow: the main repository, technical docs, and local model-iteration tool. What is not usable today is a polished public app, paid signal feed, consumer dashboard, hosted API, or no-code demo.
Closest alternatives include Numerai, QuantConnect, TradingView, and WorldQuant BRAIN. MANTIS appears stronger for contributors who want a narrow, open forecasting benchmark, but weaker in usability, commercial packaging, independent performance evidence, and general-user onboarding.
MANTIS is real and technically active, but it is not a normal-user product yet. It matters most to developers and quantitative researchers. For ordinary users, there is currently no clear app, API, or packaged signal product to try.
