AI Implementation
Implementing AI isn't just adding a model to a process.
It means reorganizing how your company decides, executes, and measures. We start with the problem, move to a solution in production, and only then talk about scaling.
Implementation: particle computer
Before we build
What we ask before we build.
- 01
What problem needs to be solved?
- 02
How does the process work today?
- 03
Which systems are involved?
- 04
Where is the data?
- 05
Who decides?
- 06
What can be automated?
- 07
Which risks need controls?
- 08
How will the outcome be measured?
The three levels
Three levels. One fits where you are today.
Comparing the levels matters more than looking at each one alone. Read the four rows to see where you stand.
| Criterion | 01 · Level 1Diagnostic | 02 · Level 2Focused Implementation | 03 · Level 3CompanyOS |
|---|---|---|---|
| Who it's for | Those who need evidence to decide where to start. | Those who already have a priority process and want results in production. | Those who want AI as a capability across the entire organization. |
| When to choose it | Before choosing a vendor or a tool. | After the diagnostic, or when the priority is already clear. | When several departments already operate with AI but lack coordination. |
| What you receive | Process map, prioritized opportunities, risks, metrics, and a roadmap. | A solution built, integrated, tested, and running in production, with measurement in place. | The operational layer: orchestration, memory, governance, and measurement across the company. |
| What you get | An informed decision. The diagnostic does not commit you to implementation. | A process running with AI and a before-and-after metric. | An organization that learns, measures, and scales with control. |
| Explore the Diagnostic | Explore Focused Implementation | Explore CompanyOS |
Departments
Where we work.
- sales
- customer service
- finance
- back-office
- operations
- logistics
- knowledge management
- software development
- document analysis
- decision support
- administrative processes
Deliverables
What we build.
We use off-the-shelf tools when they solve the problem. We build when they don't.
- automations
- agents
- copilots
- integrations
- applications
- dashboards
- workflows
- alerts
- data processing and access
- memory and context retrieval
- APIs
- custom systems
How we measure
The goal isn't to deliver an interesting demo. It's to make the solution work in your company's real operating environment.
- time
- rework
- cost
- speed
- capability
- quality
- revenue
- risk
- customer experience
Next step
Start with a diagnostic.
An operational assessment, evidence-based priorities, and a roadmap. No obligation to proceed with implementation.