AI Integration & Private AI

AI that never leaves your control

Alpine Edge helps businesses adopt AI without giving up their data. We build private, GDPR-compliant AI — deployed on your own infrastructure or cloud — so sensitive information stays in your environment and is never used to train someone else’s model. From self-hosted models to MCP servers and AI-native software, we bring the same DevOps and compliance rigour to AI that we bring to the rest of your stack.

On-prem & self-hosted LLMs
GDPR & sensitive-data handling
MCP servers & AI agents
AI-native software

Talk to us about AI

What we deliver

Four building blocks for private, production-grade AI — combined into whatever your use case needs.

Private & on-prem AI

Open models such as Llama and Mistral run inside your environment or air-gapped, with full EU data residency. Nothing is sent to third-party APIs and nothing trains external models.

GDPR & sensitive data

PII detection and redaction, air-gapped deployments, encryption with your own keys, role-based access, and full audit logging — aligned with GDPR and ISO 27001.

MCP servers & agents

Model Context Protocol servers connect your internal tools, APIs, and data to AI agents with scoped permissions and complete auditability — safe, current, and revocable.

AI-native software

Retrieval-augmented (RAG) assistants over your own documents, copilots embedded in your workflows, and the call-center AI we already run in production.

How an AI project works

Every engagement is scoped to your data and use cases, and delivered in three phases.

01. Audit

We map your use cases, data sensitivity, infrastructure, and compliance constraints, and agree the right models and architecture.

02. Build

We deploy the models, MCP servers, and software in your environment, with the security and data controls above built in from day one.

03. Run

We host, monitor, and continuously improve the system with the same DevOps discipline as the rest of your infrastructure.

Questions, answered

What is private or on-prem AI?

Private AI means running AI models inside your own infrastructure — on-premises or in your own cloud account — instead of sending data to a third-party API. Alpine Edge deploys open models (such as Llama and Mistral) in your environment so your data never leaves it and is never used to train someone else’s model.

Is Alpine Edge’s AI GDPR-compliant?

Yes. Because the models run in your environment with EU data residency, no personal data is shared with external AI providers. We add PII redaction, encryption, access control, and audit logging, and align deployments with the GDPR and ISO 27001 practices from our EU & ISO compliance work.

What is an MCP server and why would I want one?

An MCP (Model Context Protocol) server lets AI assistants and agents securely use your internal tools, APIs, and data with scoped permissions and full auditability. Alpine Edge builds MCP servers so your teams’ AI agents can act on your systems safely, instead of hallucinating or being cut off from your data.

What kind of AI-native software does Alpine Edge build?

Retrieval-augmented (RAG) assistants over your own documents, copilots embedded in your workflows, and automation. We already ship AI in production for call centers — call transcription, summarization, objection detection, lead-intent scoring, and automated QA.

How does an AI project with Alpine Edge work?

We work in three phases: an audit of your data, use cases, and constraints; a build phase where we deploy the models, MCP servers, and software; and a run phase where we host, monitor, and improve the system with the same DevOps discipline as the rest of your infrastructure.