Active development  ·  Apply AS AI Engineering

Intelligence
at scale.

We're building production-grade AI for the energy sector — augmenting engineers, automating workflows, and accelerating digital transformation across Apply's entire project lifecycle.

Explore the mission ↓ View Jira board →
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Our mission

Build intelligent tools that
augment engineers and
automate the work that slows them down.

6
platform building blocks
5+
active epics in flight
∞
engineers to augment

What we're building

Six pillars.
One platform.

A comprehensive suite of AI-powered capabilities, built for engineering at industrial scale.

🧠
AI Platform & Infrastructure
Shared MLOps/LLMOps platform: model serving, evaluation, monitoring, and a common data & feature store for every team to build on.
🔧
Engineering Assistants
AI-powered tools that help engineers search documentation, generate reports, and surface relevant project knowledge instantly.
⚡
Automation Pipelines
End-to-end pipelines that automate data collection, preprocessing, and analysis for engineering and maintenance workflows.
🔗
Integrations & APIs
Connectors to internal systems — document management, ERP, CMMS — and external data sources that feed every AI feature.
🛡️
Governance & Standards
Guidelines, templates, and review processes ensuring responsible AI development: security, data privacy, and model quality.
🛠️
Developer Tooling
Shared libraries, CI/CD templates, code standards, and contribution guides that raise the bar across every repository.

The foundation

Production-grade,
from day one.

A GitOps-managed Kubernetes platform built for scale, reliability, and zero-trust security — the same stack in CI as in production.

Orchestration
Kubernetes
GitOps · Argo CD
Pipeline Orchestration
Networking & Security
Service Mesh · Istio
Zero-Trust Access
mTLS Everywhere
Private Load Balancing
Data & AI
Distributed Compute · Spark
Open Lakehouse
LLM Serving
Feature Store
Delivery
CI/CD · GitHub Actions
Infrastructure as Code
Multi-environment Parity

Where we are

The roadmap.

From bare metal to production AI — our phased journey toward a world-class engineering intelligence platform.

✓
Phase 1 · Done
Repository & Governance Scaffold
Organization structure, repository standards, CI/CD templates, code conventions, and contributing guidelines established. The foundation every team member builds on.
✓ Complete
→
Phase 2 · In Progress — AIE-22
Kubernetes Platform Foundation
5-node Kubespray cluster managed via GitOps with Argo CD app-of-apps, Istio service mesh, zero-trust networking, and a local test harness — the same stack in CI as in production.
⬤ Active
3
Phase 3 · Upcoming
Data & AI Platform
Pipeline orchestration, distributed compute, open lakehouse architecture, feature store, and full MLOps tooling for end-to-end model lifecycle management.
Upcoming
4
Phase 4 · Future
AI Products & Engineering Assistants
Intelligent document search, automated report generation, maintenance workflow automation, and deep integration with engineering systems — putting AI directly into engineers' hands.
Upcoming

Who we are

The team.

A small, focused team moving fast — building the foundation everything else grows on.

Bjarte Haugland
Chief of AI & Technology

Oversees the high-level strategic vision and paves the way — ensuring AI delivers real value across Apply's engineering operations.

Sindre Tellevik
AI & Tech Lead

Building the entire AI platform and the services running on it — while driving user adoption and making progress visible across the organisation.

This team is growing. More roles opening as the platform matures.
"We don't build AI to replace engineers —
we build AI to make engineers superhuman."

Apply AS · AI Engineering · 2026

🎯
Production-first
Every tool ships to production. No demos, no experiments that don't scale.
🔒
Zero-trust
Security and privacy baked in from day one, not bolted on after.
🌊
Open standards
Built on battle-tested open-source. No vendor lock-in, ever.
⚡
Engineers first
Every feature validated by the engineers who use it daily.

See where we're headed.

The full backlog, sprint status, and engineering decisions live on our Jira board. We track everything.

Open Jira board →