> For the complete documentation index, see [llms.txt](https://t-matic.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://t-matic.gitbook.io/docs/projects-and-brand-dna/overview.md). # Projects Overview A project is your workspace for a single brand. It holds everything T-Matic learns and produces about that brand: the website analysis, the Brand DNA profile, every analyzed page, the knowledge graph, your Maven conversations, connected social accounts, and the content you create. If you work with more than one brand — your own and a few clients, or several products under one company — you create one project per brand. Projects are independent. Data, conversations, and connected accounts in one project never leak into another. *** ## What goes into a project When you create a project, you give T-Matic three things: * A **name** — how the brand shows up in your dashboard * A **business URL** — the brand's website, which is the starting point for analysis * An optional **description** — a short note for your team Everything else is generated for you. *** ## What T-Matic builds inside a project From the moment you create a project, T-Matic starts assembling its intelligence layer. Over the next few minutes, the project fills up with: | Layer | What it is | | ---------------------- | ------------------------------------------------------------------------------------------------- | | **Brand DNA** | The structured profile of the brand: identity, audience, voice, visual style, messaging | | **Sources** | Every page T-Matic has crawled and analyzed, processed through the source analysis pipeline | | **Knowledge Graph** | A queryable map of entities (products, audiences, competitors) and the relationships between them | | **Media library** | Brand images extracted from the site plus any assets you upload | | **Notes** | Free-form notes you and your team add to the project's knowledge base | | **Maven conversation** | The project's dedicated AI chat, grounded in everything above | You do not need to assemble these yourself. They appear as the analysis pipeline runs, and you will see status indicators on the project dashboard while it works. *** ## Project lifecycle Every project moves through a predictable set of states. You will see these reflected in the status badge on the project page. ``` Created ──▶ Crawling ──▶ Draft ready ──▶ Enriching ──▶ Complete │ ▼ In use ``` * **Created** — the project exists; the URL has been accepted * **Crawling** — T-Matic is fetching the homepage and discovering linked pages * **Draft ready** — the first Brand DNA draft is available (usually within 2–4 minutes). You can start using Maven and reviewing outputs at this point * **Enriching** — T-Matic continues crawling and analyzing the remaining key pages, refining the Brand DNA * **Complete** — the enrichment pass has finished. The Brand DNA, sources, and knowledge graph are at full quality * **In use** — the project is live. You can keep adding sources, generating content, scheduling posts, and asking Maven questions indefinitely If something fails along the way, the project shows a **Failed** state with the error detail. You can re-trigger the pipeline from the project view. *** ## Onboarding and Brand DNA The first time you open a new project, T-Matic walks you through a short onboarding flow. The goal of onboarding is to confirm and refine what the AI inferred from the website — your involvement here makes the Brand DNA more accurate. You can skip onboarding and let T-Matic use the AI-generated draft as-is, or step through and adjust the parts that matter. Once onboarding is marked complete, the project is fully ready for everyday use. *** ## What you can do inside a project Once a project is set up, it becomes the home for everything you do for that brand: * **Ask Maven questions** about the brand's voice, positioning, claims, or content gaps * **Browse sources** — read every analyzed page with its extracted facts, voice signals, and graph triples * **Explore the knowledge graph** to see how entities connect and trace each claim back to its source page * **Generate social content** — drafts that respect the brand's voice and the channel's format, ready to schedule and publish * **Connect social accounts** — link Instagram, LinkedIn, and other platforms so you can publish from the same place where the content was created * **Manage media** — organize brand images, screenshots, and assets in folders, with everything accessible to the AI when generating content *** ## Multiple projects, one workspace All projects live inside your workspace. Every member of the workspace can access every project — there is no per-project permission layer right now. If you need to separate access between teams, separate them at the workspace level. Billing (subscription and token credits) is shared across projects in a workspace. Tokens consumed by analyzing a project, generating content, or chatting with Maven all draw from the same workspace balance. *** ## Archiving and deleting You can archive a project to remove it from your active dashboard without losing its data. Archived projects can be restored at any time. Deleting a project removes everything it contains: sources, Brand DNA, graph data, conversations, generated posts, and uploaded media. Connected social accounts are disconnected. Deletion cannot be undone, so the UI asks for explicit confirmation. *** ## Where to go next * New to T-Matic? Start with the [Quick Start Guide](/docs/getting-started/quick-start.md) to create your first project * Want to understand the vocabulary used here? See [Core Concepts](/docs/getting-started/core-concepts.md) * Ready to add more pages or external content to a project? See [Connecting Your First Data Source](/docs/getting-started/connecting-data-source.md) --- # 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, and the optional `goal` query parameter: ``` GET https://t-matic.gitbook.io/docs/projects-and-brand-dna/overview.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.