Uteke FAQs

Question 1

What kind of search capabilities does Uteke offer for memory recall?

Accepted Answer

Uteke features a powerful Hybrid Semantic Search, which combines vector similarity search with FTS5 full-text search. Results are merged using Reciprocal Rank Fusion (RRF), allowing agents to find memories by meaning, keywords, or both for highly relevant recall.

Question 2

How does Uteke ensure fully offline operation without API keys?

Accepted Answer

Uteke achieves full offline capability by using ONNX embeddings for all model inference locally. This eliminates the need for any external APIs, cloud services, or internet connection for its core functions, ensuring data privacy and consistent performance.

Question 3

What are the primary advantages of Uteke over other AI memory solutions?

Accepted Answer

Uteke stands out with its single binary, zero dependencies, fully offline operation, and absence of API keys. It offers unique features like native time-travel queries, robust hybrid search, multi-agent 'Rooms', and is built in Rust for exceptional speed (~45ms recall) and efficiency, keeping all data locally.

Question 4

What is Uteke and what problem does it solve for AI agents?

Accepted Answer

Uteke gives AI agents persistent, local-first memory, preventing them from forgetting information between sessions. It enables semantic storage, recall, and search of information without cloud dependencies or API keys, keeping your AI's context always available and on your machine.

Question 5

Can Uteke be used for multi-agent collaboration or team projects?

Accepted Answer

Yes, Uteke supports multi-agent collaboration through its 'Rooms' feature. This allows memories to be grouped by specific contexts (e.g., projects, meetings) and shared among agents or team members, complete with author attribution for improved teamwork and knowledge management.

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