> For the complete documentation index, see [llms.txt](https://deepsnitch-ai.gitbook.io/deepsnitch/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://deepsnitch-ai.gitbook.io/deepsnitch/whitepaper/roadmap.md).

# Roadmap

> **The development journey for DeepSnitch AI platform**

***

## 🚀 Early Access

**Launch SnitchFeed & SnitchScan, Ethereum/BNB support**

* Deploy the first two core AI agents
* Establish foundation on primary blockchain networks
* Begin real-time surveillance capabilities
* Initial user onboarding and testing

***

## 📈 Expansion

**Add SnitchGPT & AuditSnitch, multi-chain (Solana, Base) Integration**

* Complete the core AI agent suite
* Expand blockchain network coverage
* Enhanced cross-chain monitoring capabilities
* Advanced analytics and intelligence features

***

## 🔮 Predictive Intel

**Launch SnitchCast, Advanced Predictive Analytics, Customizable alerts**

* Deploy news and alpha aggregation agent
* Implement predictive market analysis
* Advanced user customization options
* Enhanced alert and notification systems

***

## 🏛️ Institutional Tracking

**Dark Pool Tracking, Compliance Modules, Institutional Dashboard**

* Professional-grade surveillance tools
* Institutional compliance features
* Advanced tracking capabilities
* Enterprise dashboard and analytics

***


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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://deepsnitch-ai.gitbook.io/deepsnitch/whitepaper/roadmap.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.
