> 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-2-how-it-works/2.1-the-platform-at-a-glance.md).
# 2.1 The platform at a glance
Orbit is built as a stack. At the bottom is the data and the backbone that links it; in the middle, the structured records drawn from that data; above that, the agents that do the work; and across the top, the people and systems that put questions to it. Each layer rests on the one below, and the whole stack is held together by a single backbone — the entity master — that runs through all of it.
> *Caption: The Orbit stack — all data unified on one entity master, structured by agents, and served to users and systems above.*
Read from the bottom up, the architecture tells the story of the platform.
**The entity master is the backbone.** It underpins every other layer. A master record of every company and the relationships between them, it is what allows a filing, a broker note, a news item, and a price series about the same company to be recognised as belonging together. Every piece of data in the layers above is anchored to it. Because of that, nothing in Orbit sits in isolation — and adding a new source means linking it into a structure that already understands the companies it describes, not starting another silo. This is covered in 2.2.
**The data layer is one home for everything.** Public filings, news, and market data sit alongside the firm's own internal documents and any third-party feeds it brings in — all in one place, all anchored to the entity master. This is what makes Orbit *the* data layer for research rather than one more source to reconcile against the others. The same layer also holds a private space, a sandbox, where a firm's own data can live securely within the platform. This is covered in 2.3.
**The structured layer is where documents become data.** Sitting between the raw sources and the agents above, this layer is the result of the reading Orbit has already done — the structured records drawn out of documents so they can be queried, compared, and monitored without re-reading the underlying text each time. Specialist processes turn each kind of source into structured output: broker research, news flow, filings, and more. This is covered in 2.4.
**The agent layer is where the work happens.** At the top, an orchestrating agent directs specialist agents that draw on the structured layer beneath them to answer questions and run workflows. The agent system works in two modes — answering ad hoc questions across the data, or running structured workflows that produce data and reports on their own. Orbit provides off-the-shelf agents to start with, and lets every user build their own. This is covered in 2.5 through 2.8.
Above the stack are the people and systems that use it: analysts, portfolio managers, and quants working in **Orbit Insight**, and the firm's own applications and AI tools reaching the same data through the API and connectors. Whichever way the platform is approached, it is the same stack underneath, resting on the same backbone.
For simplicity, the documentation groups this stack into two layers a user deals with directly. The **Knowledge Base** is everything from the entity master up through the structured data — the connected, structured foundation. **Orbit Insight** is everything above it — the agents, the application, and the integrations through which a team actually works. The chapters that follow take each part of the stack in turn, starting with the backbone that holds it together.
---
# 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-2-how-it-works/2.1-the-platform-at-a-glance.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.