Experiments

  • Generative AI as an accessibility auditor

    We tested whether AI chat tools could replace or supplement traditional accessibility scanners, and learned that the quality of the output had less to do with the model and more to do with how precisely we asked the question.

    See experiment: Generative AI as an accessibility auditor

  • Can you just ask your database a question?

    We built a natural language interface to a legacy analytics database to find out how far plain English can get you before SQL becomes unavoidable.

    See experiment: Can you just ask your database a question?

  • Your codebase is a graph

    We mapped a codebase as a knowledge graph and queried it for structural problems, then built 21 metrics and a dashboard to make the findings actually useful.

    See experiment: Your codebase is a graph

  • Cross-tool Semantic Search

    Most teams don’t have a documentation problem. They have a documentation sprawl problem. We built a semantic search layer across Jira, Confluence, and Figma to find out how far AI can go in solving it.

    See experiment: Cross-tool Semantic Search