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Welcome to the RoboSystems Wiki!

RoboSystems is an enterprise-grade financial knowledge graph platform that transforms complex financial and operational data into actionable intelligence through graph-based analytics and AI-powered insights.

This wiki is the technical documentation for using, operating, and building on the platform. It is organized into five areas — from first-run setup through the operational API, the RoboLedger and RoboInvestor extensions, the financial-content fabric, and the document and search layer.

Getting Started & Platform

Orientation and self-hosting: stand up a local stack, learn the vocabulary, and understand the system design.

• Quick Start - From just start to your first authenticated query in ten minutes
• Core Concepts - The vocabulary: graphs, tiers, blocks, operators, operational vs analytical
• Architecture Overview - System design and components
• Bootstrap Guide - Set up AWS OIDC federation and GitHub Actions (self-hosting)

Operations Layer

The core platform API and graph management.

• Authentication & API Keys - The X-API-Key header for technical access, and the JWT boundary
• Graphs & Multi-Tenancy - The graph_id model, tiers, and subgraphs
• Graph Operations - The CQRS operation surface: backups, subgraphs, materialize
• Querying the Analytical Graph - Ad-hoc Cypher over the analytical (OLAP) graph
• Credits & Billing - The credit model: only AI operations consume credits
• AI Operators & MCP - The MCP surface and the three retrieval planes
• Pipeline Guide - Data pipelines, Dagster architecture, and custom adapters
• Custom Graph Schema - Design and build custom graph databases

Extensions Layer

RoboLedger and RoboInvestor — the graph-scoped product surfaces.

• Extensions Surface Overview - The URL topology, three sub-surfaces, and feature flags
• GraphQL Reads - Ad-hoc typed reads over the operational (OLTP) graph
• RoboLedger Operations - Command writes and analytical views (the fact grid)
• RoboInvestor Operations - Portfolios, securities, and positions
• Connecting QuickBooks Locally - Run real QB OAuth against a local stack via ngrok
• RoboLedger Demos - Synthetic-data and Seattle Method XBRL demos

Content & Contribution Fabric

The semantic content layer — how taxonomy, ledger, and report content is modeled and contributed.

• Information Blocks - The unifying envelope that ties everything together
• Taxonomy & Frameworks - The rs-gaap and fac frameworks, the library, and the Taxonomy Block
• Event-Driven Ledger - REA, the three-level ledger, and the Event Block
• Reporting & Rendering - The fact grid engine, reporting styles, and views
• Serialization & Export - Exporting blocks to XBRL and JSON-LD

Documents & Search

Unstructured content and retrieval — the institutional-knowledge layer that grounds AI.

• Search & AI Retrieval - Index documents and retrieve them through MCP tools
• Document Management - The document store over entity graphs
• File Uploads - File uploads for generic graphs
• SEC XBRL Pipeline - Working with SEC financial data

Reference

• Component READMEs - Detailed technical docs in the codebase
• API Documentation - API reference with machine-readable OpenAPI spec

Support

• Issues
• Wiki
• Projects
• Discussions