CloudShare

**The company's own team page contains a sentence most companies would not print.** Guterman, it says, purchased CloudShare from its investors for four dollars, and then built it into the market leader in laboratory environments. The company had raised around $26M across three rounds. **A business does not invent a story in which its own investors valued it at four dollars**, which is the best reason to believe it - and the ending is that it was sold to a Denver asset manager at a reported $60M to $80M after roughly a decade of bootstrapped, profitable growth.

**That sequence is worth sitting with, because it inverts the standard narrative this timeline records over and over.** Raise money, grow fast, sell. Here: raise money, have the investors write it off entirely, buy it back for a nominal sum, and then grow slowly on your own revenue until it is worth tens of millions. **The venture route is the one that gets written about, and it is not the only one that works.**

**The technical problem is specific and is one this site's readers will recognise instantly.** Enterprise software assumes a data centre: several machines, particular network topology, licences, an installed state that takes a day to reach. Anyone who has taught such a product knows the real constraint is not the material - **it is that thirty students each need a working copy of an environment that takes hours to build and that they will inevitably break.** CloudShare's answer is to snapshot a fully configured environment and hand every user an independent replica in about a minute.

**The insight in the business model is that a training lab and a sales demonstration are the same artifact.** Both are a working replica of a system the audience does not yet have, in a state that shows it doing something useful. The difference is what the audience is asked to do afterwards, and that difference is entirely in the framing rather than the infrastructure - which is why one platform serves training, presales demos and proofs of concept.

**Which is where this entry meets an argument already on this site.** A proof of concept is supposed to be a test that can fail; a demonstration is supposed to succeed. When both run on identical infrastructure, prepared by the same people, the line between them is a matter of intent rather than of setup - **and a proof of concept designed so it cannot fail is a demonstration wearing a different name.** Good lab platforms make honest testing easier and dishonest testing easier by exactly the same amount.

Customers include Palo Alto Networks, Atlassian, HP, Microsoft, RSA, Salesforce and ForgeRock - **several of which appear elsewhere on this timeline**, which is the ordinary condition of the layer this cluster documents: the companies you have heard of run on companies you have not.

**And it closes the cluster where it began.** Kryterion partners with CloudShare to add proctoring to hands-on labs, which is the industry converging on the hybrid: **the realism of a practical assessment, in a reproducible environment, with the identity verification of a supervised exam.** Every piece of that sentence is a different company, and none of them writes the questions.