# Introduction

### :map:TL;DR

Think of Zevo *as Google Maps for your codebase*. It revolutionises codebase knowledge management by offering visual insights and addressing challenges in understanding complex codebases.

### :no\_entry\_sign: **The problem** 

As tech leaders and software developers, understanding large codebases and their dependencies is crucial, especially in complex microservices and legacy code environments. Further accentuating its impact on onboarding and developer productivity. 

**Zevo replaces** 

* Outdated documentation
* Static analysis
* Peer discussions during sprint cycles

### :dart:Key Metrics addressed

* Reduces Tech Onboarding Time to Less Than a Week
* Cuts MTTR by 50%
* Minimizes Rollbacks to <5%

### :gift:Whats in offer&#x20;

Zevo.ai offers code visualisation and dependency analysis tool. It provides semantic search, clear code flow diagrams, and facilitates various workflows, enabling developers to ask questions, understand data flows, plan features, and troubleshoot issues efficiently. All in all emulating human engineer understanding.

## :rocket:[Get Started Now](https://zevo.ai/)

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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://zevo.gitbook.io/zevo-documentation/introduction.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.