Frequently Asked Questions

Find answers to common questions about Querri, from getting started to advanced deployment topics.

General Questions

What is Querri?

Querri is a self-hosted AI-powered data analysis platform that enables users to analyze data using natural language. It combines conversational AI with powerful data processing capabilities, allowing users to query databases, create visualizations, and build dashboards without writing code.

Key Features:

Natural language data queries
Multi-source data integration
Interactive visualizations
Automated reporting and scheduling
Team collaboration and sharing
Self-hosted for data privacy

What makes Querri different from other analytics tools?

AI-First Approach:

Natural language interface instead of complex query builders
AI understands context across your entire conversation
Automatically selects appropriate chart types and analyses

Self-Hosted:

Complete data privacy and control
Deploy on your infrastructure
No data leaves your environment
Customizable and white-label ready

Developer-Friendly:

Open architecture
API-first design
Docker-based deployment
Extensible connector system

Is Querri open source?

Querri is a proprietary platform designed for self-hosted deployment. While the source code is not publicly available under an open source license, it is provided to licensed customers for self-hosting and customization.

What you get:

Full access to source code
Ability to modify and customize
Self-hosted deployment
White-label capabilities

Contact sales for licensing information.

How much does Querri cost?

Querri pricing varies based on deployment type and usage:

Self-Hosted:

License fees based on user count
Infrastructure costs (your own servers or cloud)
Optional support and maintenance plans

Cloud Costs:

AI API usage (OpenAI or Azure OpenAI)
Infrastructure (if using cloud hosting)
Optional services (email, storage, etc.)

Contact sales for specific pricing: [Contact Information]

What kind of support is available?

Documentation:

Comprehensive online documentation
Installation and deployment guides
User guides and tutorials
API reference

Community Support (if applicable):

Community forum
GitHub discussions
Community Slack/Discord

Professional Support (available packages):

Email support
Priority support SLA
Dedicated account manager
Custom development services
On-site training and consulting

Getting Started

What are the prerequisites for using Querri?

For End Users:

Modern web browser (Chrome, Edge, Safari, Firefox)
Account credentials (provided by admin)
Basic understanding of your data

For Administrators:

Linux server (Ubuntu 22.04 recommended)
Docker and Docker Compose installed
Minimum 8 GB RAM, 4 CPU cores
WorkOS account for authentication
OpenAI or Azure OpenAI API access

See System Requirements for complete details.

How long does it take to set up Querri?

Quick Setup (Development/Testing):

30-60 minutes with basic configuration
Includes Docker installation and basic configuration

Production Setup:

2-4 hours for initial deployment
Additional time for:
- SSL certificate configuration
- External service setup (WorkOS, AI provider)
- Data connector configuration
- User provisioning

Enterprise Setup:

1-2 days for full production deployment
Includes security hardening, monitoring, backups

See Quick Start Guide to begin.

What’s the learning curve for users?

Non-Technical Users:

Basic queries: Minutes to start asking questions
Creating charts: 15-30 minutes
Building dashboards: 1-2 hours
Advanced features: Days to weeks

Technical Users:

SQL knowledge: Helpful but not required
API usage: Familiar patterns for developers
Data modeling: Standard concepts apply

Best Practices:

Start with sample data and examples
Use prompt suggestions and templates
Take advantage of AI’s natural language understanding
Gradually explore advanced features

Can I try Querri before deploying?

Demo Environment:

Contact sales for a demo environment
Try key features with sample data
No installation required

Self-Hosted Trial:

Deploy on your own infrastructure
Full feature access
Work with your own data
Evaluation period available

Contact sales for trial access.

Features and Capabilities

What can I do with Querri?

Data Analysis:

Query databases using natural language
Join data from multiple sources
Filter, sort, and aggregate data
Perform statistical analysis
Clean and transform data

Visualizations:

Create charts and graphs automatically
10+ chart types supported
Interactive visualizations
Export charts as images

Dashboards:

Build custom dashboards
Combine multiple visualizations
Share with team members
Schedule automated reports

Automation:

Schedule recurring queries
Automated email reports
Data refresh and sync
Monitoring and alerts

Collaboration:

Share projects and dashboards
Public sharing with links
Team workspaces
Comments and annotations

See User Guide for complete feature overview.

What AI models does Querri use?

Querri supports multiple AI providers:

OpenAI:

GPT-4o (recommended)
GPT-4o-mini (faster, lower cost)
GPT-4 Turbo

Azure OpenAI:

Same models as OpenAI
Enterprise-grade deployment
Regional availability
Enhanced security and compliance

Model Selection:

Different models for different tasks
Automatic selection based on complexity
Configurable per deployment

Data Privacy:

Your data is sent to the AI provider for processing
Use Azure OpenAI for enhanced data privacy
Consider data residency requirements
Review provider data policies

What types of data sources can I connect to?

Databases:

PostgreSQL
MySQL
Microsoft SQL Server
MongoDB
SQLite

Cloud Storage:

Google Drive
Dropbox
OneDrive
Amazon S3

Business Applications:

QuickBooks
HubSpot
Salesforce

File Uploads:

CSV
Excel (XLSX, XLS)
JSON
Parquet

APIs:

REST API connector
Custom integrations

See Connectors Reference for complete list.

What chart types are available?

Querri supports comprehensive visualization types:

Line charts (single and multi-series)
Bar charts (vertical, horizontal, grouped, stacked)
Scatter plots (with regression lines)
Pie charts and donut charts
Area charts (simple and stacked)
Histograms
Heatmaps
Box plots (statistical distributions)
Network graphs
Geographic maps

See Chart Types Reference for detailed information.

Can I export data and visualizations?

Data Export:

CSV format
Excel (XLSX)
JSON
Direct download from any query result

Chart Export:

PNG (raster image)
JPEG (compressed image)
SVG (vector graphics)
PDF (for printing)

Dashboard Export:

PDF reports
Scheduled email delivery
API access to underlying data

Projects:

Export entire project
Share via link
Clone and duplicate

What are the size limits for data?

File Uploads:

Single file: 500 MB default (configurable)
Batch uploads: Multiple files supported
Compressed files: Automatically extracted

Database Queries:

Result sets: 1 million rows recommended maximum
Pagination: Automatic for large results
Streaming: For very large datasets

Storage:

MongoDB: Effectively unlimited (hardware dependent)
File storage: Depends on configuration (S3 unlimited)
Project size: No hard limits

Performance Considerations:

Large datasets may require more processing time
Optimize queries for better performance
Use aggregations for large result sets
Consider data sampling for exploration

Data and Security

Where is my data stored?

Self-Hosted Deployment:

All data stored on your infrastructure
You control the storage location
No data sent to Querri servers

Data Components:

MongoDB: Project metadata, user data, query results
File Storage: Uploaded files (local or S3)
Redis: Temporary caching and job queues

AI Processing:

Query text sent to AI provider (OpenAI or Azure OpenAI)
Results returned to your system
Configure Azure OpenAI for enhanced data privacy

Is my data encrypted?

Encryption at Rest:

Database encryption available (MongoDB)
S3 server-side encryption (if using S3)
Volume encryption recommended (OS level)

Encryption in Transit:

All web traffic via HTTPS/TLS
Database connections support SSL/TLS
Internal service communication can use TLS

Credential Storage:

All credentials encrypted at rest (AES-256)
OAuth tokens securely stored
JWT tokens for API authentication

Recommendations:

Enable disk encryption on host
Use SSL/TLS for database connections
Enable S3 encryption
Use strong passwords and keys

See Security Guide for complete security configuration.

What compliance standards does Querri support?

Self-Hosted Benefits:

Full control over data location
Ability to implement required controls
Audit logging capabilities

Relevant Standards:

GDPR: European data privacy (data residency control)
HIPAA: Healthcare data (with proper configuration)
SOC 2: Security and availability controls
PCI DSS: Payment data (avoid storing in Querri)

Compliance Features:

Audit logging
Access controls
Data retention policies
User consent management
Data export (right to access)
Data deletion (right to erasure)

Your Responsibility:

Configure security controls appropriately
Implement required policies
Regular security audits
Maintain compliance documentation

Consult your compliance officer for specific requirements.

Who can access my data?

Access Control:

Role-based permissions
Project-level sharing
Organization boundaries
Public sharing (optional, per-item)

User Roles:

Admin: Full system access
Member: Create projects, limited admin
Viewer: Read-only access (if configured)

Sharing:

Projects shared within organization
Public links for external sharing
Permission levels (view, edit)
Revocable access

No External Access:

Self-hosted means only your users
No Querri company access to your data
No telemetry or analytics sent externally (unless configured)

See User Management for access control configuration.

How are database credentials stored?

Credential Security:

Encrypted at rest (AES-256)
Encrypted in transit (TLS)
Stored in secure MongoDB collection
Access restricted to application services

OAuth Tokens:

Securely stored per user
Automatically refreshed
Encrypted at rest
Revocable from external service

Best Practices:

Use read-only database credentials when possible
Create dedicated database users for Querri
Rotate credentials regularly
Monitor credential usage
Use least-privilege principle

See Security Best Practices.

Integration and Customization

Which data connectors are available?

See the complete Connectors Reference for details on all available connectors.

Database Connectors (Generally Available):

PostgreSQL, MySQL, Microsoft SQL Server, MongoDB, SQLite

Cloud Storage (Generally Available):

Google Drive, Dropbox, OneDrive, Amazon S3

Business Apps (Generally Available):

QuickBooks, HubSpot, Salesforce

File Formats:

CSV, Excel, JSON, Parquet

API:

REST API connector for custom integrations

Can I build custom connectors?

Current Capability:

REST API connector for most custom needs
Modify source code to add connectors (self-hosted)

Enterprise Options:

Custom connector development services
Integration with internal APIs
Legacy system connections
Specialized data sources

DIY Approach:

Use REST API connector
Implement wrapper API for your data source
Map responses to Querri format

Contact support for custom connector development.

Does Querri have an API?

Yes, Querri provides a comprehensive REST API:

API Capabilities:

Project management
Execute queries and steps
Access data and results
Dashboard operations
User and organization management
File uploads and downloads
Connector configuration

Authentication:

JWT token-based
API keys (for service accounts)
OAuth 2.0 support

Documentation:

Complete API reference available
OpenAPI/Swagger specification
Example code and SDKs

See API Documentation for details.

Can I white-label Querri?

Yes, Querri supports white-labeling:

Customization Options:

Company name and branding
Logo replacement
Custom domain
Color scheme (with code modifications)
Email templates

Configuration:

Environment variables for basic branding
Source code access for deeper customization
Custom CSS and styling

What You Can Change:

Application title and logo
Login page branding
Email sender and templates
Support contact information
Footer and legal links

See White-Label Configuration for setup details.

Are webhooks available?

Current Status:

Webhook support in development
Limited webhook functionality

Planned Capabilities:

Project completion webhooks
Data update notifications
Error notifications
Custom event triggers

Alternatives:

Use API polling for now
Scheduled queries for periodic checks
Email notifications

See Webhooks Documentation for current status.

Troubleshooting

Common installation issues

Docker won’t start:

Verify Docker and Docker Compose versions
Check system resources (RAM, CPU)
Review Docker logs: docker compose logs
Ensure ports 80/443 are available

Services fail to connect:

Verify environment variables in .env-prod
Check MongoDB and Redis are running
Review service logs: docker compose logs [service]
Ensure network connectivity between services

Authentication fails:

Verify WorkOS credentials are correct
Check redirect URI matches WorkOS dashboard
Ensure WORKOS_JWKS_ENDPOINT is correct
Review hub service logs

AI features don’t work:

Verify API keys (OpenAI or Azure OpenAI)
Check API quotas and rate limits
Ensure outbound HTTPS is allowed
Review server-api logs

See Troubleshooting Guide for complete solutions.

Why are my queries slow?

Common Causes:

Large Datasets:

Query returns millions of rows
Solution: Use LIMIT, add filters, aggregate data

Database Performance:

Source database is slow
Solution: Add indexes, optimize queries, use read replicas

Complex Operations:

Multiple joins or transformations
Solution: Simplify query, pre-aggregate data

Resource Constraints:

Insufficient RAM or CPU
Solution: Upgrade hardware, scale horizontally

Network Latency:

Slow connection to database
Solution: Move closer to data source, use VPN/direct connect

Optimization Tips:

Index frequently queried columns
Use appropriate data types
Cache common queries
Sample data for exploration
Schedule heavy queries off-peak

How do I reset a user’s password?

WorkOS-Managed Authentication:

Users reset passwords through WorkOS
“Forgot Password” link on login page
Managed in WorkOS dashboard

Admin Actions:

Access WorkOS dashboard
Navigate to Users
Select user
Send password reset email

Self-Service:

Users can reset own password
Email verification required
No admin intervention needed

See User Management for details.

What if I can’t connect to my database?

Checklist:

Verify Credentials:
- Username and password correct
- User has required permissions
- Authentication method supported
Check Network:
- Database server accessible from Querri
- Firewall allows connection
- Correct port number
- DNS resolution working
Test Connection:
- Use database client from same server
- Verify connection string format
- Check SSL/TLS requirements
Review Permissions:
- Database user has SELECT permission
- Access to specific schema/tables
- Read-only access recommended
Examine Logs:
- Querri server logs: docker compose logs server-api
- Database server logs
- Firewall logs

Common Solutions:

Whitelist Querri server IP
Use SSL/TLS for connection
Create dedicated database user
Verify network routing

See Database Integration Guides for specifics.

How do I upgrade Querri?

Upgrade Process:

Backup Data:

# Backup MongoDB
docker compose exec mongo mongodump

# Backup environment file
cp .env-prod .env-prod.backup

Pull Latest Images:
Terminal window
```
docker compose pull
```
Stop Services:
Terminal window
```
docker compose down
```
Start Updated Services:
Terminal window
```
docker compose up -d
```
Verify Upgrade:
- Check all services running
- Test login and basic functionality
- Review logs for errors

Best Practices:

Test in staging first
Backup before upgrading
Review release notes
Schedule during maintenance window
Monitor after upgrade

See Deployment Guide for details.

Deployment

Can I run Querri in the cloud?

Yes, Querri can be deployed on any cloud provider:

Supported Platforms:

AWS: EC2, ECS, EKS
Google Cloud: Compute Engine, GKE
Azure: VMs, AKS
DigitalOcean: Droplets, Kubernetes
Other: Any provider supporting Docker

Deployment Methods:

Single server with Docker Compose (simplest)
Kubernetes for high availability
Managed container services
Infrastructure as Code (Terraform)

Cloud Considerations:

Choose appropriate instance sizes
Use managed databases (optional)
Configure storage (S3/equivalent)
Set up load balancing
Enable backups and monitoring

See Installation Guide for cloud-specific instructions.

What about Kubernetes deployment?

Kubernetes Support:

Kubernetes manifests available
Helm charts (future/enterprise)
Suitable for large deployments

Benefits:

High availability
Auto-scaling
Rolling updates
Resource management
Multi-region deployment

Requirements:

Kubernetes 1.25+
Persistent volumes for MongoDB
Ingress controller
Certificate management
ConfigMaps and Secrets

Getting Started:

Convert Docker Compose to K8s manifests
Use kompose for initial conversion
Customize for your environment
Set up monitoring and logging

Contact support for Kubernetes deployment assistance.

How do I set up high availability?

High Availability Architecture:

Database Layer:

MongoDB replica set (3+ nodes)
Automatic failover
Geographic distribution (optional)

Application Layer:

Multiple server-api replicas
Load balancer (Traefik or external)
Health checks and auto-restart
Session persistence via Redis

Storage Layer:

RAID for local storage
S3 or equivalent (high availability built-in)
Regular backups

Network Layer:

Redundant load balancers
DDoS protection
DNS failover
CDN for static assets

Monitoring:

Uptime monitoring
Alerting for failures
Log aggregation
Performance metrics

See System Requirements for HA considerations.

What’s the update frequency?

Release Cycle:

Major releases: Quarterly
Minor updates: Monthly
Security patches: As needed
Bug fixes: Continuous

Versioning:

Semantic versioning (MAJOR.MINOR.PATCH)
Release tags in format: v2025.09.13.1
Development builds: date + commit hash

Staying Updated:

Subscribe to release notifications
Review changelog before updating
Test in staging environment
Plan maintenance windows

Breaking Changes:

Announced in advance
Migration guides provided
Support for previous version during transition

API and Development

Is there API documentation?

Yes, comprehensive API documentation is available:

Coverage:

All REST endpoints
Request/response schemas
Authentication methods
Error codes and handling
Rate limits
Example requests

Documentation Locations:

Interactive Documentation:

Swagger/OpenAPI UI available
Test endpoints directly
Auto-generated from code

Can I extend Querri’s functionality?

Customization Options:

Source Code Access:

Modify any component
Add new features
Customize workflows
Create custom tools

Plugin System (Future):

Custom step types
Data transformations
Integrations
UI components

API Integration:

Build external tools
Integrate with other systems
Automate workflows
Create custom interfaces

Current Capabilities:

Custom connectors via REST API
Modify source for custom steps
Extend data processing logic
Customize frontend components

Support:

Community forums for sharing
Professional services for custom development
Partner ecosystem (future)

What programming languages can I use with the API?

Any language with HTTP support:

Popular Choices:

Python: Official examples available
JavaScript/TypeScript: Node.js SDK
Go: HTTP client examples
Java: HTTP client libraries
Ruby: REST client gems
PHP: cURL or Guzzle

Example (Python):

import requests

# Authenticate
response = requests.post(
    'https://your-querri.com/api/auth/login',
    json={'username': 'user@example.com', 'password': 'password'}
)
token = response.json()['token']

# Make API call
headers = {'Authorization': f'Bearer {token}'}
projects = requests.get(
    'https://your-querri.com/api/projects',
    headers=headers
).json()

See API Documentation for more examples.

Are there rate limits on the API?

Current Implementation:

No hard rate limits (self-hosted)
Limited by your infrastructure capacity

Best Practices:

Implement client-side rate limiting
Use pagination for large datasets
Cache responses when appropriate
Avoid polling (use webhooks when available)

Recommendations:

Batch operations when possible
Use streaming for large transfers
Monitor API usage
Scale infrastructure for higher loads

Future Enhancements:

Configurable rate limits per user/API key
Rate limit headers in responses
Quota management

Getting Help

Where can I find help?

Documentation:

Support Channels:

Email support: support@querri.com
In-app help widget (if configured)
Community forum (if available)
GitHub discussions (if applicable)

Professional Services:

Consulting and training
Custom development
Migration assistance
Dedicated support

How do I report a bug?

Bug Reports:

Check existing issues (if using GitHub)
Gather information:
- Querri version
- Steps to reproduce
- Expected vs actual behavior
- Error messages/logs
- Browser/environment details
Submit report:
- Email: support@querri.com
- GitHub Issues (if applicable)
- In-app bug report (if available)

Include:

Clear description
Screenshots if relevant
Log excerpts (sanitize sensitive data)
Configuration details

Critical Bugs:

Mark as urgent/critical
Include contact information
Describe business impact

Can I request new features?

Yes, feature requests are welcome:

How to Request:

Email: support@querri.com
Feature request form (if available)
Community voting (if applicable)

Include:

Clear description of desired feature
Use case and business value
Current workarounds (if any)
Priority/importance

Process:

Review and evaluation
Community feedback
Roadmap prioritization
Development and release

Enterprise Customers:

Direct feature development
Custom requirements
Priority implementation
Dedicated roadmap input

Next Steps

Ready to get started? Here are your next steps:

Review Requirements: Check System Requirements
Install Querri: Follow Installation Guide
Configure Environment: Set up Environment Variables
Learn to Use: Read Getting Started
Explore Features: Browse User Guide
Connect Data: Set up Connectors
Build Dashboards: Create Dashboards
Use API: Explore API Documentation

Need help? Contact support or consult the comprehensive documentation.