The same colleagues. The control your information requires.
SaaS, your Azure or an on-site server is not a taste question. It is where the drawing and the order may sit. You choose by requirement, not by a demo. Colleag.ai is the same product in all three. You will recognise the salesperson who only had one hosting story, and the security lead who said no.
On-premises deployment
Microsoft Azure deployment
Hybrid and cloud options
Key benefits
- On-premises deployment for full data sovereignty
- Azure deployment in your own Microsoft tenant
- Hybrid options that keep sensitive data local
- Managed cloud deployment for teams that prefer simplicity
- Same functionality regardless of deployment model
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Where should product knowledge live, with you, in your Azure, or as SaaS? Colleag.ai is the same product in all three. It is not an ERP you move to the cloud, and not a PLM with a new hosting line. It is the colleagues, and the data stays inside the boundary you set.
Product knowledge can sit with you, in your Azure, or as SaaS. Colleag.ai is the same product in all three. What you choose is where the boundary sits for the files and the ERP read, not a new ERP in the cloud.
It is not a PLM with a new hosting line. The colleagues, the SOPs and the read-only Monitor connection come along. The data stays where you put it.
How this differs from ERP, PLM, LCM and project systems
- ERP
- ERP hosting is a different business. Colleag.ai reads your ERP where it already runs.
- PLM
- On-prem PLM does not decide where AI context may live.
- LCM
- An LCM licence does not set data sovereignty for the agents.
- Project management systems
- Jira Cloud is not an answer to where the drawing may be processed.
What Colleag.ai does here that those systems do not
- The same capability wherever you run it
- Data does not cross the line you set
- No model training on your files