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Project archive / evidence first

Systems that move
data into decisions.

A structured view of Ketut Garjita’s AI and data engineering work—organised around the problem, the pipeline, the operational boundary, and the evidence behind the result.

Inspect by technology Filter the archive when verified records are available.

02 / Case-study contract

A project card should explain the operating system, not just the stack.

When records are published, each one will be expandable from a concise architecture path into a reviewable account of inputs, transformations, controls, delivery, and trade-offs.

sources→processing→serving
01

Problem, users, and goal

The user need, the measurable or explicitly qualitative goal, and the boundary of what success means.

02

Data path and shape

Source systems, ingestion path, storage layer, transformations, and feature or model preparation steps.

03

Operations and failure boundaries

Orchestration, quality checks, observability, deployment surface, constraints, and deliberate trade-offs.

04

Evidence and access

Exact tools, outcome evidence, a GitHub repository, and a live demo link where those links are available.

03 / Evidence policy

Transparent about what is known.

No project preview images or architecture diagrams cleared the media licence gate for this page, so none are shown as decorative substitutes. The absence of an image does not become a claim about an undocumented system.

04 / Continue the review

Have a system worth building?

For collaboration, hiring conversations, or a technical walkthrough of upcoming work, start with the contact page and connect with Ketut directly.