Meet Mikka

Our AI colleague.
Built to do the work.

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.

Mikka AI operations platform bringing business work and decisions into one controlled view
Websites · SEO · Social content · Test scheduling · Human approval

Part of the operating model

A member of the team, not a demo.

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.

What she does

Mikka works across the business.

One platform coordinates several specialist services. Each has its own responsibilities, controls and evidence.

Websites

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.

SEO

Connecting effort to outcomes.

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.

Social content

Turning ideas into a managed flow.

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.

Security test scheduling

Triggering the agreed work.

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

AI is not just Copilot or a moonshot.

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.

Mikka dashboard and supervised update workflow running on private infrastructure

How she works

Serious capability needs more than a clever model.

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.

  • Defined capabilities instead of unrestricted tool access
  • Information routed according to sensitivity and purpose
  • Human approval where an action has consequence
  • Operational evidence instead of confident claims

The models are replaceable components. The capability sits in the controls, integrations and operating design around them.

What makes her useful

Designed for real work.

01

Context without unrestricted access.

Mikka can bring the right information to a task without treating the whole business as one undifferentiated data pool.

02

Automation without surrendered authority.

Routine preparation and coordination can be automated. Material decisions remain explicit and attributable.

03

Evidence instead of theatre.

System state, approvals and outcomes can be checked. A polished answer is not treated as proof that the work happened.

Why customers should care

Our advice comes from operating the thing.

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.

A practical next step

What could controlled AI do for your business?

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.