> For the complete documentation index, see [llms.txt](https://docs.orbitfin.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.orbitfin.ai/part-3-use-cases/3.2-the-use-case-library.md). # 3.2 The use-case library The previous chapters described the parts: the connected data, the off-the-shelf agents, and the Agent Builder for assembling your own. This chapter introduces what a team actually runs — the use-case library — and the rest of Part 3 walks through it. A use case, in Orbit, is not a feature or a button. It is a complete recurring workflow with a clear business outcome — a piece of research a team needs done, defined end to end, from the data it draws on to the output it produces. "Morning portfolio brief" is a use case; "earnings call analysis" is a use case. Each one corresponds to a real job a research team does, and each produces something a person can act on, not just a screen to look at. Three things are true of every use case in the library. **Each is built from agents.** A use case is assembled from the building blocks described in Part 2 — the off-the-shelf agents, combined and sequenced into a workflow that delivers a specific outcome. The agents are the parts; the use case is the finished thing built from them. This is why the library exists at all: rather than asking a team to assemble agents themselves before getting any value, Orbit ships the common workflows already built. **Each ships ready to run, and is also a starting point.** The use cases in the library are productised — a team can select one and run it as it comes, with no setup beyond pointing it at the relevant portfolio, coverage list, or universe. But none of them is fixed. Each is also a template: a starting point a team can open in the Agent Builder and reshape to its own logic — its own metrics, its own thresholds, its own definition of what matters. The library gives a team a fast start and a head start at once: run it as-is today, make it yours over time. **Each runs ad hoc or automated.** Every use case works in both modes from 2.5. A team can run one on demand — pull the morning brief now, analyse this earnings call as it happens — or set it to run on its own, on a schedule or a trigger, so the brief arrives every morning and the earnings analysis runs the moment a transcript lands. Many use cases have a natural home in one mode, but none is confined to it. The library is organised the way a research team's work is, into five groups. **Daily workflow** covers the recurring rhythm of a research day — the briefs and triage that start it. **Single-name analysis** covers deep work on one company — earnings, events, theses, diligence. **Portfolio risk** covers the view across a book — drift, concentration, exposure, and where attention is most needed. **Thematic and strategic** covers research organised around themes rather than individual names. **ESG and stewardship** covers the sustainability and engagement work that sits alongside fundamental research, including regulatory reporting. Each use case in the chapters that follow can be read against the value chain from 3.1: some do foundational work — access and extraction — at scale and on a schedule, while others reach into analysis and synthesis, connecting what they find to a portfolio, a thesis, or a theme. As you read, the useful question to hold is the one from 3.1: *how far up the chain does this take me, and across how many companies at once?* The library is the set of answers Orbit ships ready-made — and the point from which a team builds its own. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.orbitfin.ai/part-3-use-cases/3.2-the-use-case-library.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.