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

# Key Concepts

> Understand the building blocks of Spark OS

Before diving in, here are the core concepts that make up Spark OS.

## Workspaces

A workspace is your business's home on Spark. Everything lives inside a workspace:

* Your contacts and CRM data
* Your agent(s) and their configuration
* Knowledge files and documents
* Views, dashboards, and pipeline stages
* Integrations and settings

Most businesses have one workspace. Agencies or multi-brand businesses might have several.

## Agents

An agent is your AI team member. Each agent has:

* **A personality** defined in its SOUL.md — name, role, communication style
* **Instructions** in its AGENTS.md — rules, workflows, how to handle specific situations
* **Knowledge** — files you upload that teach it about your business
* **Memory** — what it remembers from past conversations and interactions
* **Tools** — integrations it can use (email, calendar, phone, APIs)
* **Schedules** — automated tasks it runs on a recurring basis

Agents are persistent. They remember context across conversations and build up knowledge over time.

## Knowledge Files

Knowledge files are documents you upload to teach your agent about your business. These can be:

* **Pricing guides** — so your agent can quote accurately
* **Process documents** — step-by-step workflows
* **FAQs** — common questions and answers
* **Company info** — about us, team structure, policies
* **Any reference material** — anything your agent should be able to look up

Your agent reads these on demand. When a question comes up that relates to your docs, it checks the relevant file before answering.

## Contacts

Contacts are the people your agent interacts with — leads, customers, partners. Each contact has:

* Basic info (name, email, phone, company)
* A pipeline stage (New Lead → Contacted → Qualified → etc.)
* A lead score (hot / warm / cool)
* Notes, tags, and custom fields
* Activity history (calls, emails, messages)

## Deals

Deals represent revenue opportunities tied to contacts. Track them through your pipeline with amounts, stages, and expected close dates.

## Tasks

Tasks are follow-ups and action items. Your agent can create tasks automatically (like "Follow up with Sarah in 3 days") and track them to completion.

## Views

Views are how you see your data. Spark supports multiple view types:

* **Table** — spreadsheet-style data view
* **Pipeline** — kanban board for stages
* **Dashboard** — widgets and charts
* **Gallery** — card-based visual layout
* **Activity** — timeline of events
* **Report** — data summaries

## Schedules

Schedules let your agent run tasks automatically — daily reports, weekly check-ins, lead monitoring, or anything you'd normally have to remember to do manually.

## The Work Tab

When your agent creates documents, reports, or other deliverables, they appear in the **Work** tab. Think of it as your agent's output folder — everything it produces is organized and accessible there.