Keeping change under control.
Mikka organises site work, draft changes, publication state and follow-ups across our websites. The work stays reviewable and the difference between a draft and a live change stays clear.
Meet Mikka
Mikka is Black Chili’s AI operations platform. She organises the work around our websites, SEO, social content and security test schedules, then brings the decisions that need a person back to us.
She is not a chatbot bolted onto a browser. She is a working system built around defined responsibilities, controlled access and human authority.

Part of the operating model
Mikka keeps work moving across services that would otherwise live in separate tools, spreadsheets and reminders. She gathers the context, prepares the next useful step and makes the state of the work visible.
People still make the decisions that carry consequence. We approve publication, customer actions and material changes. Mikka helps us reach those decisions with better context and less administrative drag.
She can organise, prepare, route, schedule and monitor. She cannot quietly expand her own authority. Every capability has a defined scope and the important actions leave evidence behind.
Useful autonomy starts with clear limits.
What she does
One platform coordinates several specialist services. Each has its own responsibilities, controls and evidence.
Mikka organises site work, draft changes, publication state and follow-ups across our websites. The work stays reviewable and the difference between a draft and a live change stays clear.
She brings together research, content opportunities, drafts, schedules, technical issues and performance evidence. That helps us distinguish activity from work that is likely to create commercial value.
Mikka develops content from approved ideas, prepares posts for review and schedules material through the publishing service once it is ready. The voice and final decision remain ours.
She can set up and trigger agreed vulnerability scan schedules in the scanning platform. Testing, validation and reporting remain specialist security work.
The useful middle
For many businesses, the real opportunity sits between a general-purpose assistant and a grand programme of transformation. It is a controlled operating layer connected to specific work.
That layer can preserve context, coordinate tools and prepare actions without giving a model unrestricted access to the business. It can make routine work faster while keeping authority where it belongs.
Not every organisation needs its own Mikka. The same design principles can be applied at a proportionate scale. Start with a useful business problem. Decide what information the system may use. Define what it may prepare and what still needs approval.
That is how AI becomes part of the operation rather than another subscription looking for a purpose.

How she works
Mikka runs through a private control layer on infrastructure we manage. Local and selected cloud models can be used according to the task, the information involved and the rules that apply.
Specialist services own their data and actions. Permissions are bounded. Suggestions and actions are separated. Decisions, outcomes and known gaps remain visible.
The models are replaceable components. The capability sits in the controls, integrations and operating design around them.
What makes her useful
Mikka can bring the right information to a task without treating the whole business as one undifferentiated data pool.
Routine preparation and coordination can be automated. Material decisions remain explicit and attributable.
System state, approvals and outcomes can be checked. A polished answer is not treated as proof that the work happened.
Why customers should care
Mikka is part of Black Chili’s operating capability. We are not presenting her as an off-the-shelf product. She demonstrates that our advice on AI governance, architecture and adoption is informed by building and running a controlled system.
We understand the practical questions because we face them ourselves. Which model is appropriate. What data may be used. Where an approval belongs. How to prove an action happened. What to do when a dependency changes or a service fails.
You may need a policy and sensible configuration. You may need one controlled workflow. You may need a private platform that joins several services together.
We start with the work, the information and the decisions. The technology follows from that.
A practical next step
Tell us where work is slow, fragmented or dependent on one person remembering everything. We will help you separate a useful AI opportunity from expensive theatre.