Frequently Asked Questions

General Questions

What is Hyperparam?

Hyperparam is the missing UI for machine learning data. It's a browser-based platform that enables data scientists and ML engineers to explore, analyze, and curate massive datasets with unprecedented speed and efficiency. Built to handle terabyte-scale datasets directly in your browser, it combines powerful AI capabilities with intuitive interfaces.

How is Hyperparam different from other data tools?

Key differentiators:

Browser-native: No installation or infrastructure required
Massive scale: Handle billion-row datasets smoothly
AI-powered: Integrated quality assessment and curation
Streaming architecture: Process data without downloading
ML-specific: Designed specifically for ML workflows

What file formats does Hyperparam support?

Currently supported:

Apache Parquet (.parquet) — Full support with streaming
CSV files (.csv) — Full support with streaming
JSON Lines (.jsonl) — Full support with streaming

Do I need to install anything?

No, Hyperparam runs entirely in your web browser. Just navigate to hyperparam.app and start working with your data immediately.

Account and Access

Do I need an account to use Hyperparam?

You can explore data without an account, but you'll need to sign in with Google to access:

AI-powered features
Chat functionality
Workspace creation
Data persistence
Export capabilities

Is Hyperparam free?

During the beta period:

All features are free with sign-in
No payment required
No limits on usage

Post-beta pricing will include:

Free tier with basic features
Pro tier with advanced capabilities
Enterprise tier with full features

How do I sign in?

Click "Chat" or any AI feature
Select "Sign in with Google"
Authenticate with your Google account
You're ready to use all features!

Is my data secure?

Yes! Security measures include:

HTTPS encryption for all transfers
User data isolation
No automatic sharing
Google OAuth for authentication
Enterprise-grade cloud storage

Data Loading and Storage

How do I load data?

Three methods:

Drag and drop: For local files
URL: Paste or click public URLs
Chat discovery: Search and load datasets

Where is my data stored?

Signed out: Processed locally in browser only
Signed in: Uploaded to secure cloud storage
URLs: Streamed directly, not copied

Can I delete my data?

Yes, you have full control over your data. Delete files from your storage at any time.

Features and Functionality

What are the main features?

Core features:

Infinite scrolling: Handle billions of rows
AI chat: Dataset discovery and analysis
Quality assessment: AI-powered scoring
Workspace mode: Edit and curate subsets
Smart export: Save curated datasets

How does lazy computation work?

In table view:

AI computations happen on-demand
Only visible rows are processed
Scrolling triggers computation
Results are cached efficiently

This allows handling unlimited data without memory issues.

How do I create a workspace?

Load any dataset
Click "Edit data in workspace"
Choose sample size
Workspace opens with full processing

Can I collaborate with others?

Currently, Hyperparam is single-user. Collaboration features are planned for future releases.

Technical Questions

Why use Parquet format?

Parquet offers:

Columnar storage for efficient compression
Streaming support
Strong types

Is there an API?

No, Hyperparam runs entirely in the browser.

Performance and Limits

Are there rate limits?

Limits based on tier (free/basic/pro/enterprise)

Export and Integration

How do I export data?

Create workspace with desired data
Apply filters and transformations
Click "Export"
Add commit message
Export to storage

What export formats are available?

Currently:

Apache Parquet
CSV
JSON/JSONL

Can I integrate with my ML pipeline?

Yes, through:

Direct file exports
URL access to processed data
Standard Parquet format compatibility

API integration planned for future.

How do I version my datasets?

Best practices:

Use descriptive commit messages
Include version in filename
Document changes in metadata
Export incrementally

Troubleshooting

How do I report a bug?

Email info@hyperparam.app
Include steps to reproduce
Mention browser and OS

Getting Help

Where can I find documentation?

This documentation site
In-app tooltips
Tutorial videos (coming soon)
Community forums (coming soon)
GitHub/Discord

How do I stay updated?

Follow @hyperparamapp on X/Twitter
Check blog for updates

Is Hyperparam open source?

Core libraries are open source:

hyparquet: JS parquet parser
hightable: React virtual table
icebird: JS Iceberg reader
hyllama: Llama.cpp model parser

The main application is proprietary.

Pricing and Business

When will pricing start?

Pricing will be introduced after beta, with notice to users. Beta users may receive special benefits.

Can I use Hyperparam commercially?

Yes, Hyperparam can be used for commercial purposes following the terms of service.