is.team vs Montage — The runtime for agentic user interfaces: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of is.team and Montage — The runtime for agentic user interfaces — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
is.team
IS.TEAM LLC
An infinite-canvas project board where AI coding agents connect over MCP, subscribe to cards and reply in chat alongside the team.
Key features
- MCP Agent Boards: Claude, Cursor and ChatGPT connect over MCP, subscribe to a board and reply in card chat while they work, so agents behave like teammates rather than external tools.
- Infinite Canvas Workspace: Tasks, notes and planning share one zoomable surface, replacing separate tracker, whiteboard and chat tools.
- AI Workflow Planner: Generates and sequences the work for a board so a project can be broken down without manual ticket writing.
- AI Card Assistant: A per-card helper that drafts, summarizes and answers questions inside the context of a single task.
- Meeting Note Taker: Captures meeting notes using one-time workspace credits and extracts actionable tasks straight onto the board.
- Per-Workspace Pricing: A flat workspace fee covering up to 15 seats on the Pro plan, so adding an engineer never triggers a surprise invoice.
- Integrations and Webhooks: HMAC-signed webhooks plus Zapier and Make connections, with API access and LLM API tokens on higher tiers.
- Real-Time Collaboration: Live multi-user editing with voice chat, screen sharing, sprints, time tracking and a timeline view.
Best for
- Agent-Assisted Development: Letting a coding agent pick up a card, do the work and report progress in the same thread the team is reading.
- Tool Consolidation: Replacing a Jira, Slack and Miro combination with a single canvas for engineering leads tired of context-switching.
- Small Team Planning: Running sprints, timelines and time tracking for a startup team on a flat monthly workspace fee.
- Meeting-to-Backlog Workflow: Turning recorded meeting notes into extracted, assigned board tasks without manual transcription.
- Automated Intake: Collecting work through embeddable forms that create cards automatically on the right board.
- Cross-Tool Automation: Wiring board events to Zapier or Make through signed webhooks so downstream systems stay in sync.
M
Montage — The runtime for agentic user interfaces
Montage
A model-agnostic SDK that renders agentic, interactive UIs, hydrates artifacts faster, and reduces token usage across underlying models.
Key features
- Model-agnostic SDK: A single SDK and runtime that works with any underlying model provider, enabling developers to render agentic UI components without locking into a specific LLM.
- Agentic UI Rendering: Renders rich, interactive components (agentic widgets) that encapsulate agent behavior, state, and UI in a reusable format for web applications.
- Faster Hydration: Optimized client/server hydration flow to initialize interactive artifacts quickly, reducing perceived latency for end users.
- Token Usage Reduction: Built-in optimizations for prompt/state management that cut token usage across models, lowering operational costs and improving efficiency.
- Stateful Artifact Management: Manages and persists the state and lifecycle of interactive artifacts and their events, simplifying developer handling of agent-driven UI.
- Seamless Front-end Integration: Designed to integrate with common front-end workflows and frameworks, allowing easy embedding of agentic interfaces into existing apps.
- Model Swapping and Fallbacks: Enables switching or combining different underlying models without reauthoring UI logic, supporting fallbacks and provider-agnostic strategies.
- Developer Tooling: Provides developer-oriented APIs and runtime controls to debug, test, and tune agentic components and their interactions.
- Single SDK to render rich, interactive agentic UI components
- Runtime that hydrates interactive artifacts faster
- Reduces token usage across underlying models
- Model-agnostic operation that works with any underlying model
- Focus on rendering agentic interfaces and interactive components
Best for
- Embedding conversational, agent-driven widgets in web apps to handle complex, interactive user workflows without rebuilding front-end UI each time.
- Prototyping agentic interfaces quickly using the single SDK to iterate on UI/agent behavior while swapping underlying models for evaluation.
- Reducing LLM operational costs by leveraging Montage’s prompt and state optimizations to cut token usage across responses and background context.
- Hydrating server-rendered interactive artifacts on the client for faster startup and seamless handoff from server logic to agent-driven interactions.
- Integrating multiple model providers and failover strategies so applications can route requests to different models without changing UI code.
- Managing long-lived, stateful agent interactions (e.g., multi-step assistants or tool-using agents) with built-in lifecycle and state management.
- Build interactive agentic user interfaces with a single SDK
- Embed agent-driven UI components into applications while minimizing token costs
- Hydrate and rehydrate interactive artifacts quickly for responsive UX
- Integrate agentic UI rendering on top of different underlying language models