Analysis Jobs

Overview#

The Analysis Jobs module provides a dedicated job tracking system for managing asynchronous AI-powered analysis operations within the Argus platform. It enables organizations to monitor and manage long-running analysis tasks with detailed progress tracking, token usage reporting, cost estimation, and structured result aggregation.

Key Features#

• Asynchronous Job Management - Track long-running AI analysis tasks from creation through completion with full lifecycle visibility.
• Progress Tracking - Real-time progress updates (0-100%) for active jobs, enabling frontend dashboards to display live status to analysts.
• Token and Cost Monitoring - Track tokens consumed and estimated costs per job, providing visibility into AI resource usage and enabling budget management.
• Multi-Tenant Support - Jobs are scoped to individual tenants for secure data isolation across organizations.
• Investigation Association - Link analysis jobs to specific investigations for contextual tracking and per-case resource attribution.
• Structured Findings - Capture job results in a structured format including entity counts, relationship counts, anomaly counts, and prediction counts.
• Aggregate Statistics - Dashboard-ready statistics including job counts by status, average duration, total token usage, and cumulative cost estimates.
• Programmable API Access - Full API support for querying jobs with filtering and pagination, and retrieving aggregate statistics.

Job Types#

• Entity Extraction - Extract entities such as people, organizations, locations, and financial instruments from text data.
• Graph Analysis - Analyze relationship graphs to identify network structures, communities, and central actors.
• Threat Modeling - Perform security threat analysis to identify vulnerabilities and attack vectors.
• Pattern Recognition - Identify recurring behavioral patterns across datasets.
• Anomaly Detection - Detect statistical outliers that may indicate fraud, insider threats, or unusual activity.
• Correlation Analysis - Correlate data from multiple sources to identify connected events and relationships.
• Predictive Modeling - Generate forecasts and predictions based on historical data and patterns.

Job Lifecycle#

1. Queued - Job created and waiting to be picked up by a worker process.
2. Running - Job actively processing with progress updates.
3. Completed - Job finished successfully with results stored.
4. Failed - Job encountered an error, with diagnostic message captured.
5. Cancelled - Job manually cancelled before completion.

Use Cases#

• Analysis Dashboard - Display a live dashboard showing all active and recent analysis jobs with progress bars, cost tracking, and result summaries.
• Cost Management - Monitor AI token usage and costs across investigations to manage budgets and optimize analysis strategies.
• Investigation Analytics - View all AI analysis jobs associated with a specific investigation to understand the analytical work performed and findings generated.
• Operational Monitoring - Track job queue depth, failure rates, and processing times to ensure healthy analysis pipeline performance.

Integration#

The Analysis Jobs module integrates with other Argus modules:

• Analysis - Provides the underlying analytical engines that create and execute analysis jobs.
• Analytics - Analysis jobs may be created by the analytics engine for scheduled or triggered calculations.
• Administration - Job queue health and statistics feed into administrative monitoring dashboards.
• Investigation Management - Jobs are associated with investigations for contextual result tracking.

Last Reviewed: 2026-02-05