Switzerland’s invisible skyline: why Zug towers over the rest

Zug is a small town on a lake with an unusually tall skyline, if you give every registered company a storey. Seven of the ten tallest invisible towers we could map stand in Zug canton, which promotes low corporate taxes to attract businesses. The highest is in neighbouring Cham, where one building has 444 active registrations.

We mapped 657,870 active registered entities to 327,735 Swiss buildings. At the busiest addresses, hundreds of businesses share a front door. What are they all doing there?

Map of Switzerland’s registered-entity concentrations, highlighting buildings in Cham, Geneva, Lucerne and Wollerau.

One tower per matched building, one unit of height per active registered entity. These are registered addresses, not occupants or jobs. Unresolved addresses are excluded. Street numbers sharing a federal building identifier (EGID) are combined. Download the imageBuilding counts (compressed CSV)

The business of selling an address

A company can pay for a registered address in Cham and have its mail sent elsewhere. At Sinserstrasse 67, easyDOMIZIL offers addresses with or without "c/o Ludwig Limbeck AG". The "c/o" names the recipient handling the company’s mail. Those clients can have letters scanned or forwarded; the package without the addition includes access to workspace.

A pharmaceutical consultant is registered at number 65 and a lift installer at number 67. The two entrances belong to the same building, the largest concentration in our data. Their registered purposes describe work that can take place well beyond Cham.

Across Zug, providers make it easy to arrange an address and administration in a canton that sells itself on tax. The register names KENDRIS Schweiz AG at Gotthardstrasse 26 as the c/o recipient for 160 entities. Sarya AG at Chamerstrasse 174 appears in the same role at another of the largest buildings.

On Baarerstrasse, eMBe Finanz offers domiciliation at number 8. That street alone has three buildings in the top ten. Zug’s appeal comes with a local industry ready to help companies establish a registered presence.

The ten tallest towers

The ten matched buildings with the most active registrations
BuildingPlaceEntities
Sinserstrasse 65 / 67Cham (ZG)444
Chamerstrasse 174 / 176Zug (ZG)424
Cours des Bastions 13Genève (GE)421
Baarerstrasse 8 / 10Zug (ZG)353
Gotthardstrasse 26Zug (ZG)340
Chamerstrasse 172Zug (ZG)327
Baarerstrasse 43Zug (ZG)312
Sihleggstrasse 23Wollerau (SZ)300
Baarerstrasse 75Zug (ZG)285
Alpenstrasse 1Luzern (LU)277
Prospex production snapshot, 5 September 2026. Street numbers belonging to the same building are combined using swisstopo’s EGID.

What a registered address tells us

For 68% of buildings on the map, there is just one registered entity. Only 117 buildings have at least 100, together accounting for about 3% of the mapped total. The spectacular concentrations are a small part of the picture.

In Zug, those concentrations fit a canton that promotes low taxes and has businesses ready to supply an address. The register does not tell us why each company chose it. Sharing an address is a normal administrative arrangement and, on its own, says nothing about wrongdoing. Counting registrations as workplaces can put economic activity in the wrong location.

Data and method

We matched active Swiss commercial-register records from Prospex’s snapshot of 5 September 2026 to swisstopo’s building-address directory, covering 89.6% of active records. Counts include registered sole proprietorships and branches; deleted records, entities in liquidation and unknown statuses were excluded, as were records without a valid UID or an unambiguous building match. The snapshot totals, exclusions and source checksum are available as JSON. To investigate another address, use Prospex’s Company API or our guide to shared registered addresses in Switzerland.

Written by

Semion Sidorenko

Semion Sidorenko is the Founder and CEO of Prospex. From data engineering to machine learning research, he spent 15 years helping companies scale up data platforms. Before founding Prospex, he worked as an ML engineer at EPFL and as an independent data engineering consultant for Swiss companies.

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