Offers an expansive infinite canvas for team brainstorming and visual workshops, but lacks Eraser's code-to-diagram automation.
#1Eraser records 534,396 monthly visits with -23.6% month-over-month growth and Freemium, Paid, Contact for Pricing pricing. Rivet.dev records 21,359 monthly visits with -44.3% growth and Freemium, Contact for Pricing pricing.

Run and scale durable AI agents on your own infrastructure
| -164.9K (-23.6%) |
| -16.97K (-44.3%) |
| Primary Market & Share | 🇮🇳 India (39.6%) | 🇺🇸 United States (39.4%) |
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| Direct Visits / mo | 267.66K | 10.71K |
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| User Rating | 4.6 | 4.5 |
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| Supported Platforms | Website | Website |
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AI diagrams and technical design docs built from your code and systems
Generate architecture diagrams, flowcharts, sequence diagrams, and BPMN from a text prompt, code, Terraform, or an uploaded PDF, Word, Excel, PowerPoint, Draw.io, or Visio file.
Build interactive maps that sync with cloud accounts, repositories, and internal catalogs so the picture stays close to the real environment, with drill-down from org level to a single container.
Paste code or connect private and public Git repositories, Confluence, Notion, VS Code, and GitHub to keep diagrams grounded in actual implementation.
Run the agent toolkit in your own infrastructure under an MIT license and let MCP-compatible clients create, search, update, and export diagrams with OAuth or API tokens.

Run and scale durable AI agents on your own infrastructure
Every Actor gets a SQLite database and a filesystem, so an agent's memory and progress survive restarts and idle periods without a separate database.
Run untrusted or AI-generated code on your own infrastructure with fine-grained control over network access, filesystem permissions, and resource limits.
A node failure reschedules its Actors elsewhere with state intact, and multi-step work replays after a crash — with no checkpointing harness to build yourself.
Address an Actor directly over HTTP or hold a live WebSocket, and use the React SDK to subscribe components to an Actor's state in real time.
Offers an expansive infinite canvas for team brainstorming and visual workshops, but lacks Eraser's code-to-diagram automation.
#1
SpecialistAutomatically embeds visual diagrams directly inside text documents, though it lacks Eraser's specialized cloud architecture focus.
#2
Free / Open-sourceThe TypeScript framework for building, deploying, and observing AI agents

Provides extensive drag-and-drop shapes and templates for general diagrams, but weaker automated code-to-diagram capabilities than Eraser.
The low-cost cloud sandbox where AI agents actually live
Combines team whiteboarding, documentation, and diagramming in one platform, but less tailored for automated codebase architecture.

Self-hosted cloud development environments and AI coding agents for enterprise teams

Persistent Ubuntu cloud VMs built for AI agent factories

Agent-native cloud infrastructure that lets coding agents run the whole backend stack

Cloud Linux VMs built for developers and their AI agents

Free / Open-sourceOpen-source tool specifically tailored for database schema visualization and ER diagrams, but lacks general system documentation features.

Stronger focus on standard Mermaid syntax and code-driven diagrams, but lacks Eraser's native autonomous architecture doc generation.
Offers an expansive infinite canvas for team brainstorming and visual workshops, but lacks Eraser's code-to-diagram automation.
SpecialistAutomatically embeds visual diagrams directly inside text documents, though it lacks Eraser's specialized cloud architecture focus.
Provides extensive drag-and-drop shapes and templates for general diagrams, but weaker automated code-to-diagram capabilities than Eraser.
The low-cost cloud sandbox where AI agents actually live
Combines team whiteboarding, documentation, and diagramming in one platform, but less tailored for automated codebase architecture.
Cloud Linux VMs built for developers and their AI agents
Free / Open-sourceOpen-source tool specifically tailored for database schema visualization and ER diagrams, but lacks general system documentation features.
Stronger focus on standard Mermaid syntax and code-driven diagrams, but lacks Eraser's native autonomous architecture doc generation.