> ## Documentation Index
> Fetch the complete documentation index at: https://docs.early-bird.space/llms.txt
> Use this file to discover all available pages before exploring further.

# What Data Is Available

> An overview of the five main Early Bird collections and the kinds of questions each can answer.

# What Data Is Available

Early Bird currently exposes five useful data collections for analysis.

## Projects

Projects are the main registry rows. A project usually represents a startup, company, or team surfaced through a program.

Representative fields:

* `projectName`
* `oneLiner`
* `description`
* `marketTags`
* `domainTags`
* `technologyTags`
* `program`
* `organization`
* `awardDate`
* `sourceUrl`
* `classificationStatus`

Best questions:

* Which startup themes show up most often in accelerator-backed programs?
* Find AI, climate, biotech, or developer-tool startups by year or organization.
* Compare category mix across different organizations or program types.

## Programs

Programs are cohort-level or program-level entities such as accelerator batches, fellowship rounds, grant rounds, and startup competitions.

Representative fields:

* `title`
* `organization`
* `category`
* `awardDate`
* `sourceUrls`
* `projectCount`
* `visibilityStatus`

Best questions:

* Which programs produce the most projects?
* Which organizations run the highest-density programs?
* Compare program categories across locations or institutions.

## Organizations

Organizations are the canonical parents of programs and projects.

Representative fields:

* `canonicalTitle`
* `category`
* `location`
* `sourceType`
* `officialSourceUrls`
* `defaultProgramCategory`

Best questions:

* Which organizations are university-backed versus independent?
* Which regions have the strongest organization coverage?
* Which organizations contribute the highest project volume?

## Dashboard Summary

Dashboard summary is a cached aggregate surface optimized for cheap analytical questions.

Representative fields:

* `totalProjects`
* `totalPrograms`
* `totalOrganizations`
* `projectsOverTime`
* `programCategoryBreakdown`
* `topOrganizations`
* `topPrograms`

Best questions:

* What are the top trends over time?
* Which organizations or program types dominate the dataset?
* How does the overall category mix change across timeframes?

## Calendar Windows

Calendar data covers program events and application windows.

Representative fields:

* `program`
* `organization`
* `status`
* `startDate`
* `endDate`
* `applicationUrl`
* `confidence`

Best questions:

* Which programs are open for applications right now?
* What deadlines are coming up next?
* Which organizations have the strongest pipeline of active or upcoming opportunities?