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To set up a collaborative AI workspace in Sparkian, create or join a team workspace, assign workspace roles, invite members, and organize ongoing work into projects. Then configure project instructions and access, choose shared model defaults, set visibility for knowledge-base sources, check your plan’s limits, and use analytics to track adoption. These steps matter because workspace members share model access and Spark usage, while workspace-visible reference material can be used by everyone on the team.
1. Choose who will own the workspace
Before creating a team workspace, decide who will be responsible for its settings and billing. Sparkian gives users a personal workspace and supports team workspaces that users can create or join. Its documentation describes Sparkian as the new name for Geekflare Chat; the steps below use the current Sparkian name.
Open the workspace-name menu in the sidebar to view workspaces, switch between them, create a workspace, manage invitations, or open settings. Workspace roles determine who can manage those controls:
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- Owner: Has full control, including billing and the ability to delete the workspace.
- Admin: Can manage members and settings, but cannot delete the workspace. Admins may invite members but cannot assign the Admin role; an Owner must do that.
- Member: Can chat and use shared projects, but does not have access to workspace settings.
Choose an Owner who can take responsibility for billing and workspace administration. Keep the number of people with elevated access aligned with the team’s needs.
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2. Create or join the team workspace and invite members
If a colleague has already created the workspace, accept their invitation and switch to it from the workspace menu. Otherwise, create a team workspace from that menu. To invite people, use the workspace menu or go to Workspace settings → Members, enter one or more email addresses, and assign each person a role. A person gets access after accepting the invitation.
Invite people before adding them to projects: project members are selected from the workspace roster, so someone who is not in the workspace must first be invited and accept access.
3. Create projects around ongoing work
Use a project for a continuing area of work that benefits from its own chats, instructions, and collaborators—for example, a product launch or a support workflow. Create a project from the Projects page, then add project members from the workspace roster.
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Set project access and instructions
Project roles are separate from workspace roles:
- Creator: Creates the project.
- Editor: Can contribute to project work.
- Viewer: Can view the project.
Set project instructions to give chats in that project consistent context, such as the audience, preferred terminology, or output format. Sparkian’s Projects documentation, accessed October 7, 2026, states that project instructions can contain up to 5,000 characters. Keep them focused on information that should guide replies across the project, rather than details relevant to only one conversation.
Project conversations are collaborative in real time for members viewing them. Use project membership to keep the people working together on a task in the same shared context.
4. Set shared model defaults and agree on usage
In workspace settings, choose the default model for new single-model chats. You can also select up to five default comparison models for multi-model chat, according to Sparkian’s Workspaces documentation accessed October 7, 2026. Choose defaults that fit the team’s common tasks, and tell members when a different model is appropriate.
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Model access and Spark costs are shared across everyone in the workspace. A team should therefore agree on sensible defaults and keep usage visible, rather than treating each member’s activity as an isolated allowance.
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Sparkian’s knowledge base accepts files and text. Each source can be set to Private or Workspace visibility. A Workspace source can be referenced by anyone in the workspace; use that setting only for material appropriate for all members. Keep material that should not be broadly available private, and check the applicable plan’s storage limit before adding sources.
Before using sensitive material with an AI model, check that model provider’s terms. Sparkian’s product page says providers’ terms vary on whether data is used to train AI models, so do not assume one provider’s terms apply to every model. Sparkian describes workspace isolation as limited to authorized people and workspaces and says conversations, files, and workspaces can be deleted; those are product statements, not an independent security or compliance assessment.
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6. Check plan limits before inviting the full team
The table shows monthly prices and limits displayed on Sparkian’s official pricing page on October 7, 2026. Prices are shown in USD; Sparkian’s product page notes that billing currency varies by region. Treat these figures as a dated snapshot and verify the current pricing page before choosing a plan.
| Plan | Monthly price | Included seats | Workspaces | Knowledge-base storage | Monthly Sparks | Team collaboration | Chat history |
|---|---|---|---|---|---|---|---|
| Free | $0 | 1 | 1 | 10 MB | 100 | No | 30 days |
| Pro | $19/month | 2 | 2 | 100 MB | 10,000 | Yes | 1 year |
| Business | $49/month | 5 | 5 | 250 MB | 25,000 | Yes | 1 year |
| Scale | $149/month | 20 | 10 | 500 MB | 75,000 | Yes | 1 year |
The pricing page lists add-on seats at $5 per month per seat on paid plans. Compare plans against the actual number of people who need access, how many workspaces you need, expected Spark usage, knowledge-base storage, collaboration, and chat-history retention; no plan is automatically the right choice for every team.
Sparkian’s plan documentation says monthly Sparks refresh each billing period and do not roll over. Purchased top-up Sparks are used after the monthly plan allowance and expire one year after purchase.
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7. Use analytics to monitor adoption and usage
Workspace analytics can help an Owner or Admin see whether the team is using its shared setup and where usage is concentrated. Available views include messages, Sparks available and used, model usage, member activity, chats, projects, images, knowledge sources, artifacts, and attachments. Filters cover date ranges up to one year in UTC and can narrow results by model, member, or project.
- Check member activity and project usage to see whether the workspace structure is being used.
- Review Sparks used alongside the monthly allowance to spot usage that may affect the team’s plan choice.
- Use model and project filters to understand where activity is concentrated.
Sparkian’s documentation describes chat and image generation as live. It described audio, video, and agents as “on the way” when that documentation was retrieved; availability can change, so check the product for current status rather than planning a workflow around those features.
Quick Recap
Sources
- Sparkian Docs: Workspaces
- Sparkian Docs: Projects
- Sparkian Docs: Knowledge base
- Sparkian Docs: Plans
- Sparkian Docs: Analytics
- Sparkian: AI Workspace Pricing & Plans
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
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