Multi-step questions, answers cited to your code
Multi-step reasoning across your entire codebase with transparent trails back to the code.
- Parse question
Decompose 'How does our payment flow work?' into retrievable sub-queries.
- Retrieve context
Pull PaymentService, OrderRouter, and webhook handlers from the knowledge graph.
- Multi-hop reasoning
Trace the chain from API entry to service to external vendor to confirmation.
- Cite & answer
Grounded answer with file:line references back to your code.
Every step in the chain cites the code it used
How CodeAlive turns a question into an answer you can audit.
Natural Language Queries
Ask in plain English. "How does our payment flow work?" returns a traced explanation, not a snippet.
Multi-Step Reasoning
Follows calls across services and dependencies, not just the file you ask about.
Grounded Responses
Every answer links to the files it used. You can verify the reasoning, line by line.
Historical Context
Pulls in commits, PRs, and discussions so answers explain why the code is the way it is.
Two modes, one knowledge layer
Pick fast or thorough, depending on how much you need to be right.
Quick Search
Fast answers for simple questions
Direct lookups and targeted retrieval when you already know roughly what you are looking for.
- Typical latency
- Seconds
- Depth of analysis
- Focused
- Single-hop retrieval against the knowledge graph
- Best for "where is this defined" style questions
- Returns code snippets with line-level references
Deep Research
Full multi-step analysis for complex queries
Multi-step investigation that walks dependencies, history, and conventions before answering.
- Typical latency
- Minutes
- Depth of analysis
- Comprehensive
- Multi-hop reasoning across services and repositories
- Best for system-level and architectural questions
- Returns a structured trail with every supporting reference
When a Stack Overflow search will not do
Questions where the answer has to be right, not just plausible.
Due diligence for acquisitions
Map architecture, dependencies, and risk areas across an unfamiliar codebase before signing.
Legacy system documentation
Reconstruct how an old system works (and why) directly from the code that still runs in production.
Compliance audits
Trace data flows and access paths through every service to answer audit questions with evidence.
Incident investigation
Follow a failing path through services and history to find the change or assumption that broke.
What Deep Research looks like in practice
Three views: the answer, the citations, and the comparison with Quick Search.


Throw the question that has been blocking the team at it
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