Turn Messy Data into Clean Insights

Helioscope uses AI to automatically label, categorize, and extract information from your data. Upload hundreds or thousands of rows and get consistent, structured results in minutes.

Perfect for analyzing customer feedback, moderating content, extracting key details from documents, or any task where you need to process lots of text the same way.

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The Problem with Processing Data Manually

Without Helioscope

✕Manually reading through hundreds of reviews or documents
✕Inconsistent labeling when different people categorize data
✕Hours or days spent on repetitive classification
✕AI responses that don't match your expected format

With Helioscope

✓AI processes your entire dataset automatically
✓Every row gets the same consistent treatment
✓Process hundreds of items in minutes, not days
✓Structured output that always matches your format

How It Works

Five simple steps to go from raw data to structured results

Step 1

Create Project

Start by creating a new project. Give it a name like "Customer Feedback Analysis" or "Support Ticket Classification". Each project keeps all your data, settings, and results organized in one place.

Organize multiple datasets per project

Step 2

Upload Data

Paste your data directly into Helioscope — one item per line. This could be customer reviews, support tickets, product descriptions, social media posts, or any text you need to analyze. You can upload up to 1,000 rows at a time.

Automatic duplicate detection

Step 3

Define Output

Tell Helioscope exactly what information you want to extract. Use the visual builder to add fields like "sentiment" (positive, negative, neutral), "category", "priority score", or any custom fields you need. This is called a schema — it's like a template that ensures every result has the same structure.

Pre-built templates available

Drag-and-drop field ordering

Step 4

Write Instructions

Write a prompt — plain English instructions that tell the AI how to analyze each item. For example: "Analyze this customer review. Determine the sentiment, identify the main topic, and rate the urgency from 1-5." Use {{input}} as a placeholder for each data row.

Version history saves all your prompt iterations

Step 5

Run & Review

Hit "Run All" and watch Helioscope process your entire dataset. Results appear in a sortable table — filter by any field, spot patterns, and export your labeled data. If you update your schema or prompt, stale results are highlighted so you know what needs re-running.

Run individual rows or batch process

Execution history for each row

What Can You Build?

Helioscope works for any task where you need to analyze text consistently at scale

Sentiment Analysis

Classify customer reviews, social mentions, or survey responses as positive, negative, or neutral.

Content Moderation

Flag inappropriate content, detect spam, or categorize user submissions by topic and severity.

Data Extraction

Pull names, dates, prices, or any structured info from unstructured documents and emails.

Support Ticket Triage

Automatically categorize and prioritize incoming support requests by urgency and topic.

Lead Qualification

Score and categorize sales leads based on their inquiry text, company size, and intent signals.

Research Coding

Code qualitative research responses, interview transcripts, or open-ended survey answers.

Ready to Process Your Data?

Create your first project in under a minute. No credit card required.

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