About
We're based in Lausanne, Switzerland.
Toby Jackson and Duncan Robinson founded AlpineEdge after more than a decade building and deploying software in industries where mistakes have consequences: finance, healthcare, education, and legal services.
We kept seeing the same pattern. Teams wanted to use AI. The technology existed. But standard cloud solutions couldn't meet their security, privacy, or compliance requirements. So they waited. Or worse — they tried to make unsuitable tools work and created new risks in the process.
We started building differently. AI that runs on-device, on-premises, or in tightly controlled hybrid environments. Systems designed from the ground up for organisations that can't compromise on data sovereignty.
Today, we work with businesses to identify where AI creates real value, determine the right architecture for their constraints, and build systems that deliver measurable time and cost savings, without introducing regulatory or security risk.
If you're evaluating whether private AI makes sense for your organisation, we'd be glad to talk.
About
We're based in Lausanne, Switzerland.
Toby Jackson and Duncan Robinson founded AlpineEdge after more than a decade building and deploying software in industries where mistakes have consequences: finance, healthcare, education, and legal services.
We kept seeing the same pattern. Teams wanted to use AI. The technology existed. But standard cloud solutions couldn't meet their security, privacy, or compliance requirements. So they waited. Or worse — they tried to make unsuitable tools work and created new risks in the process.
We started building differently. AI that runs on-device, on-premises, or in tightly controlled hybrid environments. Systems designed from the ground up for organisations that can't compromise on data sovereignty.
Today, we work with businesses to identify where AI creates real value, determine the right architecture for their constraints, and build systems that deliver measurable time and cost savings, without introducing regulatory or security risk.
If you're evaluating whether private AI makes sense for your organisation, we'd be glad to talk.
About
We're based in Lausanne, Switzerland.
Toby Jackson and Duncan Robinson founded AlpineEdge after more than a decade building and deploying software in industries where mistakes have consequences: finance, healthcare, education, and legal services.
We kept seeing the same pattern. Teams wanted to use AI. The technology existed. But standard cloud solutions couldn't meet their security, privacy, or compliance requirements. So they waited. Or worse — they tried to make unsuitable tools work and created new risks in the process.
We started building differently. AI that runs on-device, on-premises, or in tightly controlled hybrid environments. Systems designed from the ground up for organisations that can't compromise on data sovereignty.
Today, we work with businesses to identify where AI creates real value, determine the right architecture for their constraints, and build systems that deliver measurable time and cost savings, without introducing regulatory or security risk.
If you're evaluating whether private AI makes sense for your organisation, we'd be glad to talk.
Built for Regulated Environments
Where data sensitivity and compliance are non-negotiable.
That means AI must run inside client-controlled infrastructure, respect existing permissions, and remain fully auditable.
Our systems are designed around these constraints — so teams gain clarity without introducing new risk.
How We Work
Our delivery approach for regulated environments while keeping data safe and off cloud.
Our delivery approach for regulated environments
1
Understand Constraints
2
Define Scope and Outcomes
3
Build and Validate
4
Deploy to Production
Built for Regulated Environments
Where data sensitivity and compliance are non-negotiable.
That means AI must run inside client-controlled infrastructure, respect existing permissions, and remain fully auditable.
Our systems are designed around these constraints — so teams gain clarity without introducing new risk.
How We Work
Our delivery approach for regulated environments while keeping data safe and off cloud.
Our delivery approach for regulated environments
1
Understand Constraints
2
Define Scope and Outcomes
3
Build and Validate
4
Deploy to Production
Built for Regulated Environments
Where data sensitivity and compliance are non-negotiable.
That means AI must run inside client-controlled infrastructure, respect existing permissions, and remain fully auditable.
Our systems are designed around these constraints — so teams gain clarity without introducing new risk.
How We Work
Our delivery approach for regulated environments while keeping data safe and off cloud.
Our delivery approach for regulated environments
1
Understand Constraints
2
Define Scope and Outcomes
3
Build and Validate
4
Deploy to Production