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

# Bigspin Quickstart: From Sign-Up to First Report

> Go from sign-up to your first AI-generated report in minutes. Create a project, upload transcripts, and read your first analysis results.

The fastest way to understand what Bigspin can do is to see it work on your own data. This guide takes you through every step — from creating an account to reading your first report. If you have a file of AI conversation transcripts ready, the whole process takes just a few minutes.

<Steps>
  <Step title="Sign up or log in">
    Go to [app.bigspin.ai](https://app.bigspin.ai) and create an account, or log in if you already have one. After signing in, you land on the **Projects** page — your central workspace for organizing transcript analysis and accessing reports.
  </Step>

  <Step title="Create a project">
    Click **Create Project** in the top-right corner. A modal appears with the following fields:

    * **Name** — A short, descriptive label for this project (required).
    * **Description** — Optional context about what this project covers.
    * **Tags** — Optional labels to help you organize and filter projects. Type a tag and press **Add** (or hit Enter) to attach it.

    After filling in the details, you can upload transcript files directly in the modal (see the next step), or click **Create Project** to create an empty project and add files later.
  </Step>

  <Step title="Upload your transcripts ">
    Drag and drop your transcript files onto the upload zone, or click it to browse. You can add multiple files at once. Or, you can connect via a data source like LangSmith or Braintrust (scroll down for those instructions).

    **Supported formats:** CSV, TSV, JSON, JSONL, Parquet — up to 500 MB per file.

    #### JSONL format (recommended)

    Each line in a JSONL file must be a valid JSON object. Include an `id`, a `turns` array, and an optional `started_at` timestamp:

    ```jsonl theme={null}
    {"id": "t1", "turns": [{"role": "user", "content": "Hi"}, {"role": "assistant", "content": "Hello"}], "started_at": "2026-03-23T04:59:52Z"}
    ```

    Valid roles for turns: `user`, `assistant`, `human_agent`, `system`, `tool`.

    #### CSV / TSV format

    Your file needs these columns (the parser accepts flexible naming):

    | Column               | Required | Accepted names                                    |
    | -------------------- | -------- | ------------------------------------------------- |
    | Conversation ID      | Yes      | `id`                                              |
    | Conversation content | Yes      | `conversation`, `messages`, `turns`, `transcript` |
    | Conversation name    | No       | `name`                                            |
    | Timestamp            | No       | `timestamp`, `started_at`, `created_at`           |

    <Tip>
      JSONL is the most reliable format because the turn structure is explicit. Use it when you have control over the export format.
    </Tip>

    #### Connecting a data source instead

    If your traces live in LangSmith or Braintrust, click **Data Sources** on the Projects page to configure an integration. Once connected, transcripts sync automatically — no file uploads needed. See the [Integrations](/integrations/langsmith) section for setup details.
  </Step>

  <Step title="Wait for analysis">
    After you upload files, Bigspin processes your transcripts automatically. You can track progress directly in the project view. Processing time depends on the number of transcripts — most uploads complete within a few minutes.

    <Note>
      You do not need to keep the browser open during processing. Bigspin runs the analysis in the background.
    </Note>
  </Step>

  <Step title="View your first report">
    Once processing finishes, open your project and navigate to its report. The report surfaces:

    * **Patterns** — Recurring themes and topics across your conversations.
    * **Issues** — Problem areas where your AI's responses fall short.
    * **Trends** — How quality and topic distribution shift over time.

    Use these findings to inform your next prompt update, training data change, or product decision. After you make changes, upload a new set of transcripts and re-analyze to measure whether quality improved.
  </Step>
</Steps>

## What's next

<CardGroup cols={2}>
  <Card title="Core concepts" icon="book-open" href="core-concepts">
    Learn the key ideas behind Bigspin: projects, transcripts, reports, and the improvement cycle.
  </Card>

  <Card title="Connect a data source" icon="database" href="/projects/connect-data-sources">
    Set up LangSmith or Braintrust for continuous, automatic transcript ingestion.
  </Card>

  <Card title="Connect your transcripts" icon="file-arrow-up" href="/projects/upload-transcripts">
    Learn more about supported formats and how to structure your data.
  </Card>

  <Card title="API Reference" icon="code" href="/api-reference/introduction">
    Integrate Bigspin into your stack with our Projects and Transcripts APIs.
  </Card>
</CardGroup>