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

# The Kodesage engine

Platform overview

The Kodesage platform is architecturally designed for on-premises deployment, encapsulating its core functionality within Docker containerized environments for enhanced modularity and isolation. The system's logical structure is centered around a virtual machine hosting the Kodesage services, with external integration points to source code repositories, ticketing systems, and documentation.

<figure><img src="https://1498950825-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F8qhVWzMLXcYl3WBsXBHs%2Fuploads%2FIHzXKy39rlFS0D7bodKc%2FHome%20-%201d.png?alt=media&amp;token=79465c42-ceda-4ba0-a3d9-3c234feefd92" alt=""><figcaption></figcaption></figure>

Key elements of the solution include an ingestion service to process and analyze the source code, creating a searchable vector database and a comprehensive knowledge graph.&#x20;

This system architecture enables essential services such as semantic code search ("Ask Kodesage"), automated document generation, and issue ticketing integration, powered by a dedicated Large Language Model (LLM). The LLM instances are hosted separately, emphasizing the system's distributed nature, which enhances both the scalability and reliability of the service.

This design facilitates seamless integration, while the on-prem LLM is used to maintain high throughput and low latency. The clear separation of services ensures a maintainable and scalable system.


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