DecisionLedger AI vs Miro
Miro is a genuinely great place to think out loud, and we are not going to pretend otherwise. The question this page answers is what happens after the workshop. Every other canvas is a dead end. This one has an exit.
Different Problems, Different Platforms
Miro and DecisionLedger AI solve fundamentally different challenges. Here's how each platform approaches its core strengths.
- An infinite canvas that people actually enjoy working on
- Real-time collaboration built for large, live workshops
- A deep template library and a large third-party ecosystem
- Mature facilitation tooling for retros, planning, and design sessions
- Broad integration coverage with the tools teams already use
- Five one-click exits into the ledger, starting with sticky cluster to decision record, with the board kept as provenance
- Shapes bound to live decisions, KPIs, projects, model runs, knowledge base documents, and canonical datasets
- A model-bound node can be run in place on the board, through the standard plugin path, for a real run id and artifacts
- Board lifecycle (Draft, In Review, Official, Archived) with an optional approval workflow, plus a fail-closed AI gate: only Official boards are referenceable, and unknown status is treated as not referenceable
- Boards inherit platform governance: row-level tenant isolation, per-board grants, version history, edit and share audit, DLP classification, legal hold, retention, and watermarking
- A serious canvas underneath: 1,000+ shapes, 1,500+ templates, Yjs real-time multiplayer, best-effort import from Miro, Lucid, Visio, draw.io, and Mermaid
Feature-by-Feature Comparison
| Feature | Miro | DecisionLedger AI |
|---|---|---|
| What it is for | A collaborative whiteboard for visual teamwork | A collaborative canvas wired into a decision ledger |
| Infinite canvas & real-time collaboration | Core strength, and the category standard | Real-time multiplayer on a Yjs CRDT with live cursors and presence |
| Shapes & templates | Deep first-party library plus a large third-party ecosystem | 1,000+ shapes across 17 stencil libraries, 1,500+ templates across 23 categories |
| Workshop facilitation | Mature: timers, voting, and facilitation tooling | Multi-page boards, chat, timers, ranked voting, breakouts, facilitator panel |
| Bringing existing boards over | Its own board format | Best-effort import of Miro, Lucid, Visio, draw.io, and Mermaid content |
| Shapes bound to live records | Integrations push a link or an image; the embedded content stays inert | Nodes bind decisions, KPIs, projects, model runs, knowledge base documents, canonical datasets, and Google Sheets, and render the live value |
| Board lifecycle & approval | Draft, In Review, Official, Archived, with an optional approval workflow | |
| Approval state governs the AI | Only Official boards are referenceable by the assistant, knowledge grounding, and MCP tools. Unknown status fails closed. | |
| One-click exit into a record | Sticky cluster to decision record, note block to decision record, board to AI-drafted brief, page to governed knowledge base document, and a model-bound node run in place for a real run id | |
| A system of record underneath | 298 decision models, a 7-stage decision lifecycle, committee voting, and outcome tracking | |
| Enterprise governance on boards | Workspace, team, and board permissions | Row-level tenant isolation, per-board grants, version history and restore, edit and share audit logs, DLP classification, legal hold, retention policy, watermarking |
| Immutable audit of the resulting decision | WORM decision audit on S3 Object Lock with full decision replay |
Feature comparison based on publicly available documentation and product announcements.
What Happens After the Workshop
Not a cheaper whiteboard. The seam between where your organization thinks and where it keeps its record.
The Board Is the End of the Line
A great workshop produces a great board, and then the board sits there. Someone retypes the conclusion into a doc, a ticket, or a slide, and the reasoning is separated from the outcome. Decision Canvas turns a selected cluster into a decision record with the board kept as provenance.
Integrations Move Pixels, Not Meaning
The structural limit of any standalone canvas is that its integrations push a link or an image into another system. The content stays inert on arrival. Our canvas writes into the system of record, and a board's approval state governs what the AI is allowed to read back out of it.
Numbers on a Whiteboard Go Stale Instantly
A pasted metric is true for one afternoon. Bind a shape to a KPI, a project, a model run, or a canonical dataset, and the board reads the real value every time it is opened.
No Board Has an Approval State
A whiteboard is either shared or not shared. There is no notion of a board that has been reviewed and made official. Ours moves Draft to In Review to Official to Archived, with an optional approval workflow in between.
Your AI Cannot Tell a Brainstorm from a Policy
Once assistants and agents start reading your workspace, every half-finished board becomes a candidate source. Only Official boards are referenceable here, and the gate fails closed: an unknown or missing status is treated as not referenceable.
Governance Stops at the Canvas Boundary
Strategy lives on a canvas your security team reviewed separately from everything else. Boards here inherit the platform's controls: row-level tenant isolation, per-board grants, version history, edit and share audit, DLP classification, legal hold, retention policy, and watermarking.
19 Patents Pending
pending U.S. patent applications covering the decision governance platform - from plugin trust verification to MCP-governed agent gateways to domain classification guardrails.