Why did Miro sell for only 2.3x ARR?

THE SHORT ANSWER

Because a multiple prices the next five years, and Miro's core artifact stopped being readable by the thing that now does the next step. Bending Spoons is acquiring Miro at a $1.355B enterprise value on roughly $600M ARR, about 2.3x, against a $17.5B mark from January 2022. The company is profitable, holds roughly $435M in net cash, and takes close to 90% of revenue from business and enterprise customers. Fundamentals like that clear well above 2.3x routinely, so compression explains the range but not the position inside it. A whiteboard imposes no schema, which is exactly why nothing downstream can consume its output, and every decision made on a board gets re-entered by hand into a tool that has a data model.

A multiple prices the next five years, and Miro's story stopped being tellable

Bending Spoons is acquiring Miro at a $1.355 billion enterprise value against roughly $600 million in ARR, about 2.3 times revenue, five weeks after taking Airtable at $1.285 billion. Miro is profitable, holds around $435 million in net cash, and earns close to 90% of its revenue from business and enterprise customers. In January 2022 it was marked at $17.5 billion after the $400 million round ICONIQ led.

Everyone ran the compression read, and the compression read is correct. Multiples unwound, the zero-rate era priced growth, and this era prices cash flow. It is also not sufficient, because compression explains the range and not the position inside it. Software with those fundamentals clears well above 2.3x routinely. The question worth answering is why top-of-cohort fundamentals landed at the bottom of the cohort.

My answer is a product answer. A whiteboard's entire value proposition is that it imposes no schema. Anything can go anywhere. That is a real feature, it is why the format survived every attempt to replace it with structured tooling, and it is why the workshop feels good in the room. It is also precisely why nothing downstream can read the output. A board is where a decision gets made and then, always, re-entered by hand into something with a data model. Into Jira. Into a doc. Into a spec. That re-entry tax was invisible while a human was going to do the next step anyway. Once the thing doing the next step is an agent, the least machine-readable surface in the stack has the weakest story about what it becomes.

This is the same mechanism I traced through Airtable, one denomination down. Airtable's moat was accumulated human effort and agents made effort cheap. Chegg and Stack Overflow were the content version. Miro's unit is legibility.

The rubric I use: count the re-entries

Take your product's most-used surface and trace one real user decision all the way through. Where is it made, and where does a person have to type it in again before anything downstream can act on it? Count re-entries, not clicks. One is normal. More than one and you are volunteering to be the artifact layer, and the artifact layer gets priced on cash flow rather than on option value.

Most teams have never run this count, because the tax was always paid by somebody working in a different tool.

What this changed on my own product

On Heidi, the agentic platform I build, legibility is the bet rather than a feature. The positioning line I use internally is rent the model, own the company brain: the durable asset is the tenant's accumulated observation record, not the foundation model. That only holds if the record is structured well enough for every other AI tool the company uses to read from it, which is why the Cortex is entity-keyed and why agent cards get published over MCP and A2A instead of staying inside our own surface. A company brain that only our own UI can read would be a whiteboard with better branding.

The same logic drove the decision to rewrite the Signals layer rather than extend it. Signals that only render for a human to look at are display-only, which is the re-entry problem in miniature: a person reads the chart and retypes the conclusion somewhere that can act. The rework makes signals compose into derived signals and feed an autonomy gate directly, so the conclusion stays machine-consumable end to end. That was a rewrite, not additive features, and it was expensive. The Miro comp is the clearest argument I have for why it was worth it.

The part founders should actually update on

For a decade the assumed endings were an IPO or a strategic buyer who wanted the product. Airtable and Miro together say that for a large, recognizable, moderately growing collaboration company, the live bid now comes from a roll-up at two to three times ARR. Not because the product is bad, but because that is who is bidding. Funds still carrying 2021 positions should be marking to these comps rather than to the last round.

Sources: Forbes on the Bending Spoons acquisition of Miro, TechCrunch on Miro's $17.5B round, Miro newsroom, Series C.

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Last reviewed 2026-09-13 · 4 min read