Case studies

From fragmented data
to something useful.

Explore the work behind the platform. This published study follows public conversations from collection to a structured dataset for AI.

Aquin and vivly public-data case study

Aquin × vivly · Public-data research

Structuring social data for AI.

Reddit and Hacker News conversations about Meta Ray-Ban glasses, brought together into a dataset that can be inspected and used downstream.

The study follows collection with vivly, restructuring with Claude Sonnet 4.6, and ingestion into Aquin’s Dataset Inspector.

Read the case study

Follow the data through the workflow.

Collect the conversation

Bring relevant Reddit and Hacker News discussions into one research workflow.

Give it a usable structure

Restructure the collected material as JSONL for downstream inspection and AI work.

Inspect the dataset

Use Aquin’s Dataset Inspector to examine the resulting records before the next step.

This study covers public-data preparation. For Backup & Recovery, Data Archiving, or AI Connectivity in your own environment, explore the product documentation or bring your workflow to a demo.

What would useful data look like for your team?

Start with the records, systems, and outcome that matter to you.

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