# Claude, ChatGPT, Copilot and Mistral for real estate and construction

> Which model does which job better — measured on contracts, correspondence, the Microsoft tenant and data residency.

- Kategorie: Comparisons
- Autor: Robert Schröder
- Letzte Prüfung: 2026-09-20
- Basis: Fragmente ai-models__*.html
- URL: https://saits.ai/wissen/vergleich-claude-chatgpt-copilot-mistral

## 01 Why the question is put wrongly

"Which model is best" leads nowhere; the question is which model should do which job in your company.

## 02 The four in one sentence each

Claude reads long documents, ChatGPT drafts and handles day-to-day work, Copilot works where Outlook, Teams and SharePoint already run, and Mistral is the European route when data residency carries the decision.

## 03 Job 1: long documents

Leases, bills of quantities and due diligence folders need context across a hundred pages and a pointer back to the passage.

## 04 Job 2: correspondence

Tenant enquiries, client communication and replies to prospects need tone and volume, not depth.

## 05 Job 3: work inside the existing Microsoft tenant

When the files are already in SharePoint and the permissions already stand, going through Copilot saves a second copy of the data.

## 06 Job 4: scanned and photographed papers

Site reports, delivery notes and old contracts come in as images and have to come out as data — here Mistral's OCR is our route.

## 07 Data residency compared

All four can be run in European regions, Copilot stays inside the client's tenant — but only Mistral also has a European provider. What a provider's seat means for your data is in [US providers and data residency](/wissen/datenstandort-und-us-anbieter).

## 08 Cost

Licence costs differ less than the cost of building the same workflow twice.

## 09 Control

The same rule applies in all four cases: the system prepares, a person approves.

## 10 Our rule

The job decides the model, not the name on the label.

## 11 When none of the four fits

If no data may leave the building, the comparison falls away and what remains is a self-hosted open model.

## 12 The table

| Job | Claude | ChatGPT | Copilot | Mistral |
|---|---|---|---|---|
| Long documents | Our route | Possible | Inside the tenant | Possible |
| Correspondence | Possible | Our route | Inside the tenant | Possible |
| Work inside the Microsoft tenant | No | No | Our route | No |
| Scanned papers | Possible | Possible | Possible | Our route (OCR) |
| Image analysis | Possible | Possible | Possible | Possible |
| Provider's seat | USA | USA | USA | France |
| Operating region | European region | European region | Client's Microsoft 365 tenant | France |
| Control | System prepares, person approves | System prepares, person approves | System prepares, person approves | System prepares, person approves |

The assessments in this table come from our own project experience, not from an external benchmark. Concrete prices are deliberately left out, because they date quickly.

Which model fits your process is decided by your process, not by this table.

[All models in one overview](/wissen/ki-modelle-und-datenstandort)