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DataLyra
Clarity in Every Byte.
DataLyra is an open-source, self-hosted, end-to-end encrypted AI data platform built as a modular system of independent but interoperable components. Each module is responsible for a specific layer of functionality, enabling scalability, extensibility, and secure customization while maintaining strict privacy and local execution guarantees.
1. Core Modular Architecture
DataLyra is structured around a layered modular design:
- Interface Layer → User interaction, dashboards, and query input
- Intelligence Layer → AI reasoning, natural language processing, and query planning
- Data Layer → Data ingestion, storage, and transformation
- Security Layer → Encryption, authentication, and access control
- Execution Layer → Query execution, analytics processing, and compute orchestration
- Extension Layer → Plugins, models, connectors, and automation modules
Each layer operates independently but communicates through controlled encrypted interfaces.
2. Interface Layer Module
Responsible for all user-facing interactions.
Components
- Web-based UI for dashboards and query interfaces
- Natural language input system
- Visualization renderer
- Report generation interface
Responsibilities
- Capture user queries
- Display results securely
- Render dashboards and insights
- Support interactive exploration
Key Properties
- Stateless by design
- Fully encrypted input and output flow
- Compatible with plugin-based UI extensions
3. Intelligence Layer Module
Responsible for AI-driven reasoning and interpretation.
Components
- Natural language understanding engine
- Query translation system from natural language to structured queries
- Insight generation engine
- Predictive analytics subsystem
Responsibilities
- Interpret user intent
- Generate optimized data queries
- Detect patterns, anomalies, and trends
- Produce explainable AI outputs
Key Properties
- Runs on self-hosted AI models
- Model-agnostic architecture
- Supports locally hosted models such as LLaMA and Mistral
- Fully local inference compatible
4. Data Layer Module
Responsible for all data ingestion and management.
Components
- Database connectors for SQL, NoSQL, files, and APIs
- Schema detection engine
- Data normalization pipeline
- Indexing and caching subsystem
Responsibilities
- Aggregate multi-source data
- Maintain structured representations
- Optimize data access patterns
- Support real-time or batch ingestion
Key Properties
- No external data transmission by default
- Schema abstraction layer for unified querying
- Encryption-aware storage handling
5. Security Layer Module
Responsible for encryption, authentication, and system integrity.
Components
- End-to-end encryption engine
- Local-only key management system
- Role-based access control (RBAC)
- Audit logging system
Responsibilities
- Encrypt data at rest and in transit
- Manage cryptographic keys locally
- Enforce user permissions
- Maintain tamper-resistant logs
Key Properties
- Zero-knowledge architecture
- No external key escrow
- Fully self-hosted security boundary
6. Execution Layer Module
Responsible for running queries and processing data.
Components
- Query execution engine
- Distributed computation handler
- Caching and optimization layer
- Streaming result processor
Responsibilities
- Execute structured queries
- Optimize performance for large datasets
- Manage computation workloads
- Stream results in real time
Key Properties
- Local execution
- Parallelizable workload design
- Resource-aware processing
7. Extension Layer Module
Responsible for modular expansion of the system.
Supported Extension Types
- Database connectors
- Visualization generators
- Workflow automations
- Domain-specific AI models
- Federated learning modules
Responsibilities
- Extend system capabilities without modifying the core
- Provide sandboxed execution environments
- Maintain encryption compliance
- Enable community-driven enhancements
Key Properties
- Strict sandbox isolation
- Opt-in permissions model
- No default external network access
- Fully versioned and replaceable modules
8. Workflow Automation Module
A specialized extension category for automation pipelines.
Capabilities
- Scheduled analytics jobs
- Event-triggered workflows
- Multi-step query pipelines
- Alert generation from data conditions
Constraints
- Must execute within a sandbox
- Must respect encryption boundaries
- Must log all execution events locally
9. Federated Learning Module (Optional)
Enables distributed AI improvement without exposing raw user data.
Capabilities
- Model parameter sharing without raw data sharing
- Encrypted update aggregation
- Cross-instance learning improvements
Constraints
- Fully opt-in participation
- No raw dataset transmission
- Local rollback support for models
10. System Communication Model
All modules communicate through:
- Encrypted internal message bus
- Strict API contracts between layers
- Controlled data serialization formats
- Permission-aware routing layer
No module can bypass the security or encryption layer.
11. Design Principles
DataLyra is built on the following principles:
- Modularity: Every system component is replaceable and extensible
- Privacy First: No data leaves the self-hosted environment by default
- Encryption Everywhere: All data flows are encrypted by default
- Explainability: AI outputs must be interpretable and transparent
- Local Control: Users own their infrastructure, models, and data
Specification Branding License (SBL)
Standard
- Fully AGPL-3.0+ compliant system
- Copyleft enforced for network deployments
- Required attribution to Roxanne Ardary and roxanneardary.com
Optional
- Specification Branding License (SBL)
- Attribution-free commercial deployment
- Pricing based on scale, usage, and deployment scope
- DataLyra Specification
License & Notice Requirements
DataLyra is released under the GNU Affero General Public License v3.0 or later (AGPL-3.0+). By contributing to this project, you agree that your contributions will also be released under this license.
Please note the following:
- All contributions must comply with the AGPL-3.0+ terms.
- Under Section 7 of the license, all redistributions, forks, and derivative works must preserve attribution to Roxanne Ardary and roxanneardary.com.
- DataLyra specifications are free to use with attribution. A Specification Branding License can be negotiated upon request.
- The project’s NOTICE.md file tracks attribution requirements and contributor acknowledgments. Any update that adds new contributors or modifies attribution should also update NOTICE.md.
- When submitting a pull request, ensure that any new files maintain the attribution requirements where applicable.
- Network-deployed versions of this software must remain fully AGPL-3.0+ compliant, including providing source code for modifications when required by the license.
For full legal details, refer to the AGPL-3.0+ license and the project’s NOTICE.md file.
Notice – DataLyra
Attribution Requirement: Under Section 7 of the AGPL 3.0+ license, all redistributions, forks, and derivative works, including network-deployed versions of this project, must provide attribution to Roxanne Ardary and roxanneardary.com.
Contributors
This file tracks contributors and their specific contributions to the project.
- Roxanne Ardary, roxanneardary.com – March 10, 2026
Created the repository for DataLyra. Designed the open-source, self-hosted, end-to-end encrypted AI platform for secure data analytics, natural language querying, and multi-source data orchestration while preserving complete user data sovereignty. - CamelAI, camelai.com
Inspired sections include AI-driven query suggestions, multi-database support, and natural language-to-SQL mapping. - [Add other contributors here] – [Date]
[Describe contribution in one sentence]
License – DataLyra
This repository is licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).
Key Points:
- You are free to use, modify, and distribute the code.
- All redistributions, forks, derivative works, and network-deployed versions must also be licensed under AGPL-3.0+ and provide attribution to Roxanne Ardary and roxanneardary.com as required under Section 7 of the license.
- The software is provided “as is,” without warranty of any kind.
For the full license text, see GNU AGPL-3.0 License.