Architecture

Product Architecture

How Method’s primitives compose into the products and applications you interact with.

Overview

Method’s architecture follows a layered composition model. At the base are atomic primitives — Tools, Tasks, Operations, Objects, Issues, and AI Agents. These primitives combine to form applications (like Operator, Explorer, and the Bastion Dashboard), which in turn are packaged into Products (Bastion and Reaper).

This layered approach means that the same underlying building blocks power both defensive and offensive workflows. Data collected through one product is immediately available in the other, because both draw from the same Ontology and Ledger.

High-level view

High-level product architecture
Product Architecture — High Level

From the bottom up:

  1. Jackals (security agents) execute Tools, which produce raw data
  2. The Task Engine orchestrates Tool execution, often leveraging AI Agents and the Analysis Engine
  3. All data flows into the Ledger and is materialized into the Ontology
  4. Explorer and Operator provide user-facing interfaces over this data
  5. Products (Bastion and Reaper) package these experiences for specific security outcomes

Detailed view

Detailed product architecture
Product Architecture — Detailed

The detailed view shows how each primitive interacts with the others:

  • Tools produce structured output that feeds the Ledger
  • The Ledger materializes data into the Ontology (knowledge graph)
  • Tasks orchestrate multiple Tools in sequence or parallel, with dependency management
  • AI Agents use the Ontology and Tool Library to reason about next steps, governed by Policies
  • Operations coordinate Tasks and direct Tool execution in real-time through Operator
  • Issues are derived from Ontology data through a mix of rule-based and AI-powered analysis

Why this matters

This composition model has several practical implications:

  • Reusability: A Tool written for Bastion’s automated scanning works identically in a Reaper operation or an AI Agent workflow
  • Data continuity: Objects discovered during a Reaper operation are visible in Explorer; Issues found during automated Tasks can be investigated in Operator
  • Extensibility: New capabilities are added by introducing new Tools or Tasks, which automatically compose with existing applications
  • Governance: Because AI Agents use the same Tools and operate on the same Ontology, they can be governed with the same guardrails as human operators