Alaz FAQs

Question 1

What kind of knowledge does Alaz manage and store?

Accepted Answer

Alaz manages a comprehensive range of knowledge, including reusable code patterns, encountered errors/decisions (episodes), step-by-step workflows (procedures), persistent facts (core memories), and lessons learned (reflections). It also supports cross-project knowledge promotion.

Question 2

Can Alaz integrate with my existing AI coding assistant?

Accepted Answer

Yes, Alaz is designed for seamless integration. It offers MCP endpoints and hooks, with explicit support for popular platforms like Claude Code, allowing your AI assistant to leverage its persistent memory for enhanced performance.

Question 3

What are the key features of Alaz's search pipeline?

Accepted Answer

Alaz features a unique 6-signal hybrid search pipeline, fusing FTS, dense vector, ColBERT MaxSim, graph expansion, RAPTOR, and memory decay. This ensures highly accurate, comprehensive, and resilient context retrieval, even with individual service failures.

Question 4

What is Alaz and how does it help AI coding agents?

Accepted Answer

Alaz provides long-term memory and context injection for AI coding agents, enabling them to overcome session-based forgetting. It automatically learns from past coding transcripts and injects relevant knowledge into new sessions.

Question 5

How does Alaz autonomously learn from coding sessions?

Accepted Answer

Alaz’s autonomous learning pipeline parses session transcripts to extract structured knowledge like patterns, episodes, procedures, core memories, and reflections. It includes built-in deduplication and contradiction detection to refine this knowledge.

Alaz

Alaz

Key Features

Use Cases

Key Features

Use Cases