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

# Quick Start: Create Your First Caplena Project

> Create a project, upload your data, generate topics with AI, review assignments, and share insights in reports to turn open-ended feedback into results.

Caplena helps you quickly turn open-ended survey responses, reviews, and other unstructured text into clear, actionable insights. This quick-start guide will walk you through the essentials so you can start uncovering what really matters in your data.

## 🎥 Prefer Video?

Watch a quick video below for a guided demo:

<iframe src="https://www.loom.com/embed/927281338f314055a959c279123d926d" title="Loom video player" frameborder="0" className="w-full aspect-video rounded-xl" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen />

***

## Step 1: Create a New Project

1. From your **Project List**, click **New Project**
2. Enter a **project name** (e.g., *NPS Survey Analysis*)
3. *(Optional)* Add **project context** – e.g., the goal, audience, or product you're analyzing. This helps generate more relevant insights
4. Set the **project language** (this determines how responses are analyzed)
5. *(Optional)* Enable:
   * **Translation** – if your data includes multiple languages
   * **Anonymization** – to automatically mask personal information

[Learn more about project setup →](/get-started/starting-a-new-project/setting-up-a-project)

***

## Step 2: Upload and Validate Your Data

1. Upload your file (Excel, CSV, etc.) or connect an integration
2. Caplena will auto-detect open text columns. Select which ones to analyze
3. You can use additional columns (e.g., age, gender) for filtering/segmentation
4. Click **Validate**, then **Continue**

<Tip>
  Keep an ID column if you'll re-upload updates later.
</Tip>

[Learn more about data upload →](/get-started/file-import)

***

## Step 3: Generate Topics with AI

1. Click **Start Analysis**
2. Choose one of the following:
   * **Start from scratch** – Caplena auto-generates topics
   * **Import** a predefined topic collection
   * **Reuse** topics from a previous project
3. Review the topic structure. Caplena organizes topics into categories. You can:
   * Rename, merge, or delete topics
   * Update topic descriptions
   * Create custom categories

If **sentiment detection** is enabled, comments are automatically marked as *positive*, *neutral*, or *negative*.

[Learn more about topic generation →](/topic-assignment/understanding-the-basics/starting-the-analysis)

***

## Step 4: Review AI Assignments

1. Open the **Topics** view
2. **Check topic descriptions** to make sure they make sense
3. **Check coverage** – if \~90% of rows have topics, you're in great shape
4. **Spot-check 10–15 responses** to make sure assignments make sense
5. *(Optional)* Use **AI certainty** – rows with low confidence might reveal topics that need better descriptions
6. **Focus on weak spots** – review topics with low coverage or unclear descriptions

<Tip>
  Improving topic quality leads to stronger insights in reports.
</Tip>

Want AI to take the first pass instead of reviewing manually? Click the magic-wand icon next to the **AI Score** to have the [Topic Critique Agent](/insight-and-reports/insight-agent/topic-critique-agent) diagnose and fix weak spots for you.

[Learn more about fine-tuning →](/topic-assignment/new-ai/how-to-ensure-high-quality-results-with-the-new-llm)

***

## Step 5: Visualize & Share Insights

1. Go to **Reports** and create a new one (from scratch or a template)
2. Use **Edit Mode** to customize charts or apply filters
3. Create **segments** to compare groups or timeframes
4. Share reports with internal or external stakeholders

[Report-building guide →](/insight-and-reports/creating-and-customizing-reports/creating-reports)

***

## Step 6: Do More with Agent

**Agent** goes beyond Q\&A — it's the same AI you may have already used in Step 4 to critique your topic assignment. Ask it to explore your data using natural language:

> "What are customers saying about delivery time?" "Why are promoters happy?"

It can also build Smart Columns for you from a plain-language description, answer questions about Caplena itself, and be shared with stakeholders scoped to a filtered report.

<Tip>
  Perfect for quick deep-dives, fixing topic quality, or stakeholder demos.
</Tip>

[Agent overview →](/insight-and-reports/insight-agent/insight-agent)


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