Tensorus Usage Guide
Learn how our innovative system works and how it can transform your data processing capabilities.
Unlike traditional SQL, NoSQL, and vector databases, Tensorus is an innovative approach that converts all data into tensors (multi-dimensional arrays) and processes them through specialized AI agents.
This approach offers several advantages:
- Efficient representation: Tensor data structures can efficiently represent complex, multi-dimensional data.
- AI-native processing: Tensors are the native format for machine learning models, enabling seamless integration with AI systems.
- Collaborative intelligence: Specialized AI agents work together to process, analyze, and learn from your data.
- Continuous learning: The system evolves and improves as it processes more data over time.
Tensorus is powered by a network of specialized AI agents, each with a specific role in the data processing pipeline:
- Data Ingestion Agent: Processes and validates incoming data files, preparing them for tensor transformation.
- Tensor Transformation Agent: Converts data into optimal tensor representations based on the data's characteristics.
- Operation Learning Agent: Learns and optimizes tensor operations based on usage patterns and data characteristics.
- Query Processing Agent: Interprets natural language queries and translates them into tensor operations.
- Orchestration Agent: Coordinates all agent activities and ensures efficient collaboration.
How to Use the System
Upload Your Data
Upload your data files with descriptions to help the agents understand the context and content of your data.
Start by navigating to the Data Upload tab in the dashboard. You can upload various types of data:
- Tabular data (CSV, Excel)
- JSON data
- Text corpus
- Image datasets
- Time series data
Important: Include a detailed description of your data to help the agents understand its context, structure, and meaning. The more information you provide, the better the system can optimize the tensor representation.
Tensor Transformation
The system automatically converts your data into the most appropriate tensor representation.
After uploading, the Tensor Transformation Agent analyzes your data and converts it into an optimal tensor representation. This process involves:
- Determining the appropriate dimensionality
- Selecting the optimal tensor structure
- Applying appropriate transformations
- Optimizing for sparsity and efficiency
You can view the transformation results in the Tensor Visualization tab, which provides interactive visualizations of your tensor data.
Agent Learning
The agents learn various tensor operations based on your data characteristics.
The Operation Learning Agent continuously learns and optimizes tensor operations for your specific data. These operations include:
- Indexing and retrieval strategies
- Regression and classification models
- Clustering and dimensionality reduction
- Anomaly detection algorithms
- Time series forecasting methods
You can monitor agent activities and learning progress in the Agent Network tab.
Query Your Data
Use natural language to ask questions about your data and receive insights.
In the Query Interface tab, you can interact with your data using natural language instead of complex query languages. Example queries include:
- "Predict sales for the next 30 days based on historical patterns"
- "Find anomalies in the transaction data"
- "Cluster customers into segments based on behavior"
- "What's the correlation between price and demand?"
- "Summarize the key insights from this dataset"
The Query Processing Agent interprets your natural language query and translates it into appropriate tensor operations.
Explore Insights
Review automatically generated insights and visualizations derived from your tensor data.
The Data Insights tab provides automatically generated visualizations and insights derived from your tensor data, including:
- Dimension analysis charts
- Data distribution visualizations
- Key insights extracted from tensor operations
- Query result summaries
- Anomaly detection results
These insights help you understand your data better and make informed decisions based on the tensor analysis.
Advanced Features
Continuous Learning
The system becomes more intelligent over time as it processes more data and learns from user interactions.
Multi-Modal Data Support
Process and analyze different types of data (text, images, time series) within the same tensor framework.
Tensor Operations API
Advanced users can directly access tensor operations through a programmatic API.
Data Lake Integration
Scale to data lake levels with distributed tensor processing capabilities.
Ready to Get Started?
Try our interactive demo to experience the power of Tensorus firsthand.
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