We work out which decisions in your operation are actually costing you money, then build the systems that fix them.
The advantage is not in the tools. It is in knowing which part of your operation to point them at, and being right about it before the money is spent.
No reseller agreements. No platform quotas. When we recommend a tool it is because it is the right tool, and when the honest answer is to do nothing yet, we say that too.
25 years delivering enterprise technology at scale. We have run these systems in production, not just drawn them on slides. It changes the advice.
The technology question comes last. First we find where judgement is being spent on work that does not deserve it, and what that is costing you every week.
Every engagement leaves you with something you own. Documented workflows, trained people, and enough understanding to make the next call without us.
Most organisations arrive somewhere in the middle of this list. Some have a roadmap and no controls. Some have agents already running and no idea what they cost. Start where you actually are.
Advise
Know where AI will pay, and in what order.
We work through your operations to find where AI creates measurable value, then rank the candidates on impact and feasibility.
An independent review of your architecture and data, telling you what is ready today and what has to change first.
A sequenced plan tied to your business goals, with the investment case, the dependencies and the decision points set out.
Assure
Put AI into production without inheriting risk you cannot see.
Clear policy, ownership and decision rights covering how AI is approved, monitored and retired across your organisation.
An assessment of your AI systems against your data protection and regulatory obligations, with the gaps prioritised and costed.
Build
Prove it works before you commit to it.
A short, fixed scope pilot that puts a working agent in front of real users and produces evidence you can take to a budget decision.
The validated pilot taken into production, with the integration, controls and documentation your team needs to own it.
Sustain
Agents drift, costs creep, and someone has to be watching.
Ongoing oversight of accuracy, reliability and adoption, reported against the outcomes the system was funded to deliver.
Regular tuning of models, prompts and routing to hold quality up and running cost down as the platforms change underneath you.
A periodic check that live systems still meet the policy and compliance position you signed off.
Available at any stage
Capability you keep after we leave.
Short sessions that give leadership teams a working grasp of what AI can and cannot do, and what it asks of them.
Hands on training for the people who will use and maintain these systems day to day.
A structured programme that moves a team from supervised use to independent delivery.
Most organisations start with the first. A few need the second, and some need both at different points.
A start, an end, and an outcome agreed before we begin. Workshops, pilots, production builds and managed operations all run this way, priced to the scope rather than the hours, so you know what you are committing to before you commit.
This is how most of our work runs. The five steps below are the path through it.
Some organisations do not need a project. They have a technology function that already works and a board asking what they are doing about AI, and what they need is judgement in the room when the decisions get made.
Fractional CTO and technical advisory work. Technology strategy and roadmap, architecture and vendor decisions, security and compliance posture, and the board level reporting that goes with them. From someone who has carried the operational responsibility, not just the recommendation.
Not sure which one fits your situation? That is usually the first conversation.
Book a conversation →Each step is short and each one ends with a decision you make. Nothing commits you to the next stage before you have seen the last one.
A short call or meeting. We hear what your business does and what you are trying to change. You hear how we work. Both sides work out whether there is something here worth doing together.
Two or four hours, in person wherever possible. We pick one domain or business function where the cost of operations is highest, and take it apart with the people who actually run it. You leave with the candidates ranked and a case with numbers attached.
A two week sprint that puts something working in front of real users. Not a demo and not a slide. Enough evidence to make the investment decision either way.
The validated pilot taken into production and integrated into the way your team already works, with the guardrails, human checkpoints and documentation the work genuinely requires.
We hold the system to the outcome it was built for, correct it when it drifts, and extend it as the work moves on. Or we hand it over and your team runs it.
Most engagements are shorter than the client expected, and easier to explain to a board.
Kairnix is led by Marc Linnegar, who has spent 25 years in enterprise technology across Africa, Europe, Australia and Asia. Most recently a director of cloud and managed services go to market, building the platform propositions that large organisations run their operations on.
He started Kairnix on a simple observation. The organisations getting real value from AI are rarely the ones spending the most on it. They are the ones who picked the right problem. The technology is seldom the hard part. Choosing where to point it is.
Kairnix is based in Singapore and works with organisations that want AI to show up where it counts. Faster answers for customers, better decisions under pressure, and capability their competitors do not have.
Tell us what is slow, expensive or inconsistent in your operation. If we can help, we will tell you how. If we cannot, we will tell you that instead.
