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title: 'How It Works'
---
import { VersionBadge } from "/snippets/version-badge.mdx"
Prowler Lighthouse AI integrates Large Language Models (LLMs) with Prowler security findings data.
Behind the scenes, Lighthouse AI works as follows:
- Lighthouse AI runs as a [Langchain agent](https://docs.langchain.com/oss/javascript/langchain/agents) in NextJS
- The agent connects to the configured LLM provider to understand the prompt and decide what data is needed
- The agent accesses Prowler data through [Prowler MCP](https://docs.prowler.com/getting-started/products/prowler-mcp), which exposes tools from multiple sources, including:
- Prowler Hub
- Prowler Docs
- Prowler App
- Instead of calling every tool directly, the agent uses two meta-tools:
- `describe_tool` to retrieve a tool schema and parameter requirements.
- `execute_tool` to run the selected tool with the required input.
- Based on the user's query and the data necessary to answer it, Lighthouse agent will invoke necessary Prowler MCP tools using `discover_tool` and `execute_tool`
Lighthouse AI supports multiple LLM providers including OpenAI, Amazon Bedrock, and OpenAI-compatible services. For configuration details, see [Using Multiple LLM Providers with Lighthouse](/user-guide/tutorials/prowler-app-lighthouse-multi-llm).
Lighthouse AI can only read relevant security data. It cannot modify data or access sensitive information such as configured secrets or tenant details.
## Set Up
Getting started with Prowler Lighthouse AI is easy:
1. Navigate to **Configuration** → **Lighthouse AI**
2. Click **Connect** under the desired provider (OpenAI, Amazon Bedrock, or OpenAI Compatible)
3. Enter the required credentials
4. Select a default model
5. Click **Connect** to save
For detailed configuration instructions for each provider, see [Using Multiple LLM Providers with Lighthouse](/user-guide/tutorials/prowler-app-lighthouse-multi-llm).
### Adding Business Context
The optional business context field lets teams provide additional information to help Lighthouse AI understand environment priorities, including:
- Organization cloud security goals
- Information about account owners or responsible teams
- Compliance requirements
- Current security initiatives or focus areas
Better context leads to more relevant responses and prioritization that aligns with your needs.