You need to resolve a specific decision or a stalled AI initiative.
AI consultingBLACKOPS SOFTWARE / AI SYSTEMS & AUTOMATION
AI implementation.
Turn your AI plan into a solution employees can use every day.
Discuss your projectAdvice, strategy or implementation?
Several initiatives need priorities, ownership and a roadmap.
AI strategyThe process is selected; you want to test and introduce a solution.
AI implementation (this service)UNDERSTAND THE SERVICE
How do you move an AI pilot into everyday use?
AI implementation connects a chosen application to real data, users and working agreements. Beyond the model call, we implement access controls, error handling, checks and handover for daily operations. We start with a bounded test set and a fallback route. Expansion follows only when the agreed quality, cost limits and human checks work in practice.
When it is a good fit
A process has been selected, a process owner is involved and representative data is available. The goal is an application staff can actually use.
When to take a different approach
If the problem is still unclear, start with an assessment or strategy. Missing permission or source access must be resolved first.
Compare your options
Choose based on the task, the people involved and what you can maintain.
| Approach | Useful when | What to consider |
|---|---|---|
| Prototype | Test one technical assumption. | Not automatically suitable for production data or daily use. |
| User pilot | Test quality and working practices within a limited scope. | Needs representative examples and explicit boundaries. |
| Production rollout | Pilot criteria are met and maintenance has an owner. | Requires monitoring, support and a recovery procedure. |
What we need to start
- Approved data and access rights for the selected application.
- Examples with expected outputs and difficult exceptions.
- An owner for incidents, costs and quality checks.
How to assess the result
- The application passes a documented representative test set.
- Uncertain results go to a person or a safe fallback route.
- Access, logging, cost limits and rollback are tested.
SCOPE & INVESTMENT
What determines the cost?
A useful estimate starts with the scope. We distinguish development work from recurring usage and operating costs. These are the main drivers:
- Number of systems and data types.
- Consequences of errors and required review.
- Monitoring, usage volume and handover to maintainers.
01 / PROBLEM & POSSIBILITIES
Your challenge.
A practical application.
A successful AI demo needs to become a manageable business solution.
Turn your AI plan into a solution employees can use every day. We agree what the solution should do, which information it needs and how the result will be assessed.
THE QUESTION WE ASK FIRST
What quality must the solution achieve before it can be used?
02 / FROM QUESTION TO SOLUTION
An approach with
clear steps.
You stay informed about decisions, progress and delivery. We adapt the scope to your organisation.
Map processes and goals
What quality must the solution achieve before it can be used?
Assess value and feasibility
We use representative examples and discuss the results, making assumptions and limitations visible before proceeding.
Build and measure a pilot
We document the agreed outcomes, responsibilities and next steps.
03 / A PRACTICAL FOUNDATION
Designed for your
systems and requirements.
Technology that fits
Your existing process documentation, email, business software and available data sources.
Security and control
We identify the data needed, limit access and arrange human review of sensitive or uncertain results.
A possible application
A successful AI demo needs to become a manageable business solution. The project can start with one focused component. Together we assess whether expanding it makes sense.
Illustrative scenario; not a published client case.04 / WHAT TO EXPECT
Your questions.
Clear answers.
Is a working demo enough to go live?
No. A demo only shows that a scenario can work. Rollout also requires checks for exceptions, access rights, outages, costs and maintenance ownership.
Where do we start with ai implementation?
What quality must the solution achieve before it can be used? We discuss this together, define the scope and establish what is needed for an informed proposal.
What does the project cost?
The investment depends on scope, existing systems, data quality and required integrations. Your proposal separates the work, assumptions and any recurring usage or operating costs. A useful estimate requires an understanding of your situation.
How long does delivery take?
We agree a schedule once the scope and dependencies are known. System access, team availability and acceptance testing are included in the plan. Where possible, we start with a focused first step.
Can we keep our existing systems?
Your existing process documentation, email, business software and available data sources. We investigate the possibilities and limitations before proposing a technical approach.
What happens after delivery?
You receive a handover explaining the solution and its documentation. Maintenance, support and further development are agreed separately, including responsibilities and how errors will be handled.