THE CHALLENGES
Every use case is built by hand
Your core systems were built for reporting. Each new AI use case means months of integration work before the business sees anything.
AI raises the bar
The business already expects conversational BI, natural language queries and AI development on your own data. Each of these requires an architecture that serves data in a governed and secure way.
Tool sprawl slows development
Without shared interfaces and a common framework, every team builds its own solutions. Maintenance eats development time, and no one is in control of the whole.
Knowledge depends on key people
Only the person who built the pipelines knows how they work. When they leave, development stops and the risk stays with you.
Modern data architecture is not an IT project. It decides whether your AI is reliable, scalable and worth the investment.
OUR PRINCIPLES
How we design data architecture that survives production.
Every Arked architecture engagement follows the same principles. They ensure you get a platform that runs in production, not a diagram left on a slide.
01
Business use cases first
We do not design architecture for its own sake. Every solution is sized for real use cases, so the value shows in the business, not just in an architecture diagram.
02
Technology independent
Arked is technology independent. We recommend solutions based on your data, your team and your needs, not partner quotas. You avoid vendor lock-in and keep your options open.
03
We build, not just design
The architects who design your architecture also implement it. You get a solution that runs in production, not a target state left on slides.
04
Cost aware
Architecture decisions determine what data and AI cost years from now. We account for long-term cost impact and optimise the cost structure for your needs.
How we put data architecture into practice.
Engagements range from a short audit to ongoing architecture leadership. Most clients start with a technology audit and expand from there.
Choose the service that fits your situation
Technology audit
1-6 weeks
We conduct a thorough audit of your current infrastructure. We identify the bottlenecks and the areas where improvement delivers the most value.
You get a prioritised roadmap that tells you what to fix first and why.
AI and data architecture modernisation
Project, scope agreed together
Our senior architects turn your systems into a modern platform for operational use and growth. We design a scalable, cloud-native architecture that breaks down silos and lowers the cost of every new use case.
Senior architects and interim leaders
Ongoing, flexible
Our technical leaders do not just design, they deliver. We build scalable data pipelines and services and integrate modern AI technologies with strong DevOps practices. Fixed monthly price, flexible commitment. Senior-level data leadership is also available part time through our CaiO as a Service model.
CLIENT FEEDBACK
A senior-level data and AI partner for demanding projects
9.8 / 10
Average client rating for delivered AI and data engagements.
REFERENCES
CASE Keva: AI-Ready Data Strategy and Data Governance Transformation
Building a stronger AI-ready data foundation: The challenge Keva has a long history of leveraging [...]
05
Jun
Jun
Case HSL: AI and Data platform modernisation
Scattered data slowed development and was not AI-ready HSL’s data was scattered across multiple platforms [...]
19
May
May
Flexible Architecture and Capability Design, Case Example: Keskisuomalainen
Today, many organizations struggle to turn their business vision and digital strategy into practical capability [...]
16
Sep
Sep
