Catenary vs Numerous.ai: Features, Pricing & Which Is Better (2026)

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

Catenary

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.

Freemium

A spreadsheet plugin that embeds ChatGPT into Google Sheets and Excel to extract text, categorize data, and generate formulas.

Chat Integration: Embed ChatGPT-style conversational prompts directly in Google Sheets and Excel cells to query, transform, and generate content from spreadsheet data.
Formula Generation: Automatically produce complex spreadsheet formulas from natural-language descriptions, reducing time spent crafting and debugging formulas manually.
Text Extraction and Categorization: Extract structured text from messy cells, categorize free-form responses (e.g., survey replies), and populate consistent labels across rows.
Batch Processing: Apply transformations, prompts, or categorization rules across entire ranges or columns to automate repetitive data-cleaning and classification tasks.
Summaries and Natural-Language Reports: Generate row-, column-, or sheet-level summaries and human-readable explanations of datasets for faster insights and reporting.
Cross-platform Support: Works inside both Google Sheets and Microsoft Excel, enabling teams to use the plugin across common spreadsheet environments.
Bring ChatGPT functionality directly into Google Sheets and Excel
Extract text from spreadsheet cells using natural-language prompts
Categorize and label rows or cells based on content
Generate spreadsheet formulas and functions via natural language
Enable in-sheet AI-assisted data-cleaning and analysis

Survey Analysis: Automatically categorize open-ended survey responses into topics or sentiment labels and create summary counts within the spreadsheet.
Formula Assistance: Convert a plain-language calculation request into a working spreadsheet formula (e.g., VLOOKUP, INDEX/MATCH, nested IFs) to accelerate spreadsheet building.
Data Cleaning: Extract and standardize text from inconsistent cells (addresses, product descriptions, notes) across large ranges using natural-language prompts.
Report Generation: Produce executive-ready summaries and written explanations of sales, financial, or operational data directly from sheet data.
Bulk Labeling: Apply consistent tags or classifications to thousands of rows (e.g., product categories, customer types) with a single prompt and range selection.
Ad-hoc Analysis: Ask natural-language questions about a dataset (e.g., 'Which regions underperformed last quarter?') and receive interpreted results or formulas inserted into the sheet.
Automatically extract structured information from messy text in cells
Categorize product descriptions, support tickets, or survey responses
Generate or suggest Excel/Sheets formulas based on plain-language requests
Accelerate spreadsheet data-cleaning and transformation tasks
Embed conversational or generative assistance into spreadsheet workflows