Asimov vs Catenary: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Asimov and Catenary — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Asimov

ASIMOV Platform

Freemium

Foundational search and module platform enabling AI agents to discover, compose, and manage neurosymbolic capabilities.

Foundational Search: A dedicated search layer that indexes modules, capabilities, and artifacts so AI agents can discover relevant components at runtime or during planning.
Polyglot SDKs: Language SDK support (notably Rust SDKs) to build, register, and integrate neurosymbolic modules into agent pipelines and services.
Module CLI Management: Command-line tools for module lifecycle tasks—publishing, versioning, dependency resolution, and module snapshots for reproducible deployments.
Snapshot Tooling: Snapshot CLI for capturing module states and dependencies to enable reproducible rollbacks and audited deployments of agent stacks.
Installer Integration: Packaging formulas and installers (Homebrew, Scoop) to simplify local developer setup and runtime installation on developer machines and CI.
Module Ecosystem & Specs: A module specification and repository model that standardizes how cognitive, symbolic, and neural components are described and consumed.
Trust & Verification Primitives: Built-in emphasis on versioning, provenance, and auditable snapshots to improve reliability and governance of neurosymbolic agents.
Foundational search for agent knowledge
Indexing and retrieval for agent workflows
API access for integrations
Documentation and terms of service referencing subscriptions/billing
Foundational search functionality targeted at AI agents

Agent Capability Discovery: Allow autonomous agents to query a searchable registry to locate vetted neurosymbolic modules (e.g., planners, perception connectors) during task planning.
Building Neurosymbolic Pipelines: Developers assemble pipelines combining neural components and symbolic logic using SDKs and module specs to create explainable agent behaviors.
Module Lifecycle Management: Teams publish, version, and snapshot modules via the CLI to ensure reproducible experiment runs and safe rollouts to production agents.
Edge and Developer Deployment: Use Homebrew/Scoop installers or packaged snapshots to rapidly provision developer machines or edge nodes with specific module sets.
Auditability & Governance: Capture module snapshots and provenance for compliance, postmortem analysis, and to enable trusted rollbacks after model or module updates.
Integration with Rust Workflows: Rust developers build high-performance modules using the ASIMOV Rust SDK and manage them via the platform CLIs.
Provide retrieval/knowledge access to autonomous agents
Index and surface documents for agent decision-making
Integrate search into multi-agent systems and pipelines
Provide retrieval/search primitives for autonomous agents to obtain context and knowledge during decision-making

Freemium

Local-first spatial IDE that orchestrates Claude Code, Codex, Cursor, and other coding agents on an infinite canvas with visual context wires.

Infinite Canvas: Terminals, Monaco editors, browsers, and git worktrees float on one pannable, zoomable surface so every agent stays visible at once.
Context Wires: Drag a directed wire between panels to pass context to another agent, set to relay automatically or act as a standing permission.
One-Click Worktrees: The New Task button creates an isolated branch, working directory, and agent, colour-coded across sidebar, dock, and canvas.
Monaco Diffs: VS Code's editor inside the canvas with git-aware file tree and side-by-side diffs of everything an agent touched.
Maestro Mode: One agent recruits, briefs, and wires a team of up to ten helpers, with an editable approval card before every action.
Multi-Project Parallelism: Run several projects at once, each with its own canvas and multiple isolated branches, with state preserved on switch.
Local-First Privacy: No account, no telemetry, and zero bytes of source code, prompts, or keys sent anywhere; only two outbound hosts total.
Bring Your Own Keys: Agent CLIs talk directly to Anthropic, OpenAI, or Google with your own keys, or to Ollama and LM Studio on localhost.

A developer runs three coding agents on separate branches simultaneously and watches all of them without losing track of any.
An engineer delegates a specific subtask from one agent to another by dragging a wire instead of copy-pasting context between windows.
A team working under strict data policies needs an agent IDE that provably never uploads source code.
A solo builder ships several experiments in parallel isolated worktrees without polluting the main working tree.
A reviewer wants side-by-side diffs of agent-authored changes before deciding what to keep.
A user orchestrates a self-organizing squad of agents while keeping human approval on every structural change.