AI
cognira
Better thinking, better answers
- Category
- AI
- Stage
- Growth
- For
- People and developers seeking a privacy-conscious, locally served AI assistant that learns from confirmed chat feedback.
About
Teach it once, see what stuck, and watch verified memory improve a model served from a single iMac. cognira Entity runs it on your hardware. Free to use, no credit card.
Features
- Problem
- Users cannot tell whether an assistant retained or applied a preference.
- How it works
- Confirmed preferences, facts, and words enter private memory immediately; replies that use a memory identify it and offer one-tap Forget.
- Result
- Users can teach the assistant once and verify what influenced a response.
- Why
- Makes personalization inspectable and reversible.
- Problem
- A bad or sensitive chat could corrupt learning.
- How it works
- Sensitive, unsafe, malformed, and down-rated replies are excluded; shared knowledge requires independent teaching and checks before promotion.
- Result
- Learning can improve the product without allowing a single chat to rewrite it.
- Why
- Separates immediate private usefulness from guarded system-wide learning.
- Problem
- Cloud AI can require sending conversations to provider infrastructure.
- How it works
- cognira Entity runs models, memory, embeddings, and optional weight retraining locally in a sealed binary.
- Result
- Users can run a self-learning assistant with nothing leaving their machine.
- Why
- Keeps the local product’s data and learning on the user’s disk.
- Problem
- Developers need programmatic access to the model.
- How it works
- The Platform API provides an OpenAI-compatible endpoint with named keys and usage graphs.
- Result
- Developers can integrate the model without changing to a proprietary API shape.
- Why
- Lets developers use cognira Retrain from their own code.
Screenshots
