Enterprise Architecture with an
Autonomous AI Reasoning Engine
Bridge conceptual business capabilities to physical runtime assets. Built in Go, Rust, and Python with portable
.tvwx repositories, live switching across SQLite, PostgreSQL, MySQL & Redis, a 36-cell
6×6 Orthogonal Architecture Matrix, and autonomous 30d/90d architectural drift forecasting.
Automatic Package Nesting
Drop any object into a Package on the canvas to automatically establish parent containment and a formal Nesting («contains») relationship. Move it out to cleanly detach.
On-Canvas Handle & Shortcuts
Drag the top-center ↻ rotation handle with 15° snap (or hold Shift for 1° precision), press R / ⇧R, or set exact degrees in the Inspector & Selection Bar.
Click any cell below to inspect how the Rust CSR Graph Core enforces multi-layer vertical lineage from Scope to Operations.
| Perspective \ Dimension | C1: WHAT (Data) | C2: HOW (Function) | C3: WHERE (Network) | C4: WHO (Actors) | C5: WHEN (Events) | C6: WHY (Motivation) |
|---|---|---|---|---|---|---|
| R1: Executive Scope | R1:C1Domain Entities | R1:C2Value Streams | R1:C3Operating Regions | R1:C4Business Units | R1:C5Business Cycles | R1:C6Strategic Drivers |
| R2: Business Concepts | R2:C1Semantic Data | R2:C2Service Domains | R2:C3Channel Network | R2:C4Role Taxonomy | R2:C5Business Events | R2:C6Governance Policies |
| R3: System Logic | R3:C1Canonical Schema | R3:C2App Components | R3:C3Logical Topology | R3:C4System Access | R3:C5State Transitions | R3:C6System Constraints |
| R4: Technology Physics | R4:C1Physical DDL | R4:C2Runtime Services | R4:C3Cloud Nodes | R4:C4Runtime Principals | R4:C5Execution Timing | R4:C6Physical Targets |
| ID | Object Name | Object Type (Enum) | Stereotype «» | Package (Enum) | Status (Enum) |
|---|---|---|---|---|---|
| #108 | 💠 Payment Execution Router | Component ▾ | «ServiceDomain» | Transaction Hub Core ▾ | Implemented ▾ |
| #114 | 💳 Canonical Payment Object | Class ▾ | «TransactionHubObject» | Canonical Data ▾ | Approved ▾ |
Designed for Principal Architects & Autonomous AI Agents
Every diagram, canonical schema, capability map, and portfolio investment lives in a single transactional graph model with full ⌘Z / ⇧⌘Z undo/redo history.
High-Performance Rust CSR Graph Core & Semantic Lineage
Powered by a memory-mapped Compressed Sparse Row (CSR) bidirectional graph engine in Rust (tview-graph-core), TreeviewEA executes Tarjan Strongly Connected Components (SCC), Brandes Betweenness Centrality, Degree-Normalized PageRank, and 6-stratum vertical lineage verification from Executive Scope down to Operational Telemetry in sub-millisecond time.
Dual-Direction AI Drift Engine
Starts out-of-the-box with local ONNX Runtime inference and seamlessly switches to Ollama + Redis Vector Graph or Hybrid Bi-Directional mode to predict 30d/90d architectural drift and apply 1-click optimizations.
Precision Diagramming & 360° Rotation
Drop objects into Packages to automatically capture «contains» relationships. Pull connector lines to any perimeter point for exact edge-snapping or drop on the body for dynamic auto-snap. Rotate any object 0°–359° via the on-canvas ↻ handle or R / ⇧R shortcuts.
Transaction Hub, BIAN v12, TOGAF 10 & ISO 20022
First-class support for the Transaction Hub canonical schema ($.onBehalfOfPayer, $.returnSpecificInfo, $.enrichedDataInExchange, $.exchangeRate), BIAN Service Domains, ArchiMate 3.2, SysML, BPMN 2.0, and AWS icons.
39-Tool Model Context Protocol (MCP)
Built-in stdio and HTTPS/SSE MCP server exposing 39 structured tools so Claude Desktop, Cursor, and autonomous agent teams can inspect, scaffold, audit, and optimize your architecture live.
Portable Single-File .tvwx + Live Multi-Backend Switching
Start with a self-contained .tvwx file on your laptop and hot-switch or bi-directionally transfer your entire 20-table tview_* repository to enterprise database backends at any time.
📁 Portable .tvwx & SQLite
Zero-configuration local file management with WAL journaling, instant snapshots, and legacy .qea / .eapx import.
🐘 PostgreSQL + pgvector & MySQL 8
Enterprise relational persistence for multi-architect teams with full DDL generation and canonical schema synchronization.
⚡ Redis Stack Vector & Graph
Sub-millisecond graph adjacency lists, HNSW semantic embeddings, and pub/sub drift telemetry under tview:ea:* keys.
Modern, Open-Source & AI-Native
Built from the ground up to replace legacy desktop modelers and static drawing tools.
| Capability | TreeviewEA v2.5.0 | Legacy Desktop EA Tools | Cloud Drawing Whiteboards |
|---|---|---|---|
| 6×6 Orthogonal Matrix & Lineage Verification | ✓ Automated via Rust CSR Graph Core | Manual static matrices | ✕ No semantic metamodel |
| Autonomous 30d/90d Architectural Drift ML | ✓ Local ONNX + Ollama/Redis Hybrid | ✕ None | ✕ None |
| Portable File + Live DB/Redis Switching | ✓ .tvwx + SQLite / Postgres / MySQL / Redis | Proprietary Windows-only DBs | Cloud-locked SaaS only |
| Canvas Package Containment & Smart Snap | ✓ Auto «contains», Edge Snap & 360° Rotate | Rigid manual connectors | Visual-only (no repo sync) |
| Built-In Model Context Protocol (MCP) Server | ✓ 39 Native Tools (stdio & TLS SSE) | ✕ None | Limited read-only APIs |
| License & Extensibility | ✓ AGPL-3.0 Open Source (Go + Rust + Python) | Proprietary per-seat licensing | Proprietary subscription |
Download the Bundled macOS Installer or Build from Source
Install the native signed macOS application bundle (TreeviewEA.app) via the drag-and-drop .dmg disk image, or launch directly from the CLI.
TreeviewEA for macOS (Apple Silicon)
Includes the native macOS WebKit Studio, compiled Go server, Rust tview-graph-core engine, Python Deep ML Drift worker, and sample TransactionPlatform-Architecture.tvwx repository.