Introduction to SIFRA
SIFRA (Synthetic Intelligence for Real-time Analysis) is an autonomous data scientist engine designed to bypass the latency of human analysis. Unlike traditional LLM wrappers, SIFRA utilizes HDP-FusionNet, a proprietary vector-based intent engine, to perform hard mathematical computations, forecasting, and anomaly detection instantly.
Deterministic
Results are mathematically verifiable, not hallucinated.
Zero-Config
Auto-detects schema, seasonality, and correlations.
Core Architecture
The system is composed of three primary nodes operating in parallel:
HDP-FusionNet
High-Dimensional Processing layer. It ingests raw CSV/JSON streams and converts them into normalized vector tensors for analysis.
HDS-Unity Matrix
The central state machine. It orchestrates the flow between the forecasting engine, the anomaly detector, and the visualization renderer.
Quick Start Guide
Follow this protocol to initiate your first analysis run.
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1
Upload Dataset
Navigate to the Command Center and upload a CSV file. Ensure the first row contains headers.
Date,Revenue,Cost 2024-01-01,1500,800 2024-01-02,1800,900 -
2
Select Operation
Choose "Deep Analysis" or "Forecasting" from the Input Parameters panel.
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3
Initialize Engine
Click the "Initialize Engine" button. The system log will display real-time processing events.
API Reference
Titan Tier Required
Direct API access is restricted to Titan subscribers. Recruit and Commander users must use the web interface.
Authentication
Include your Secret Key in the header of every request.
Prediction Endpoint
Send data for real-time inference using a pre-trained model.