Four phases.
One accountable team.
ADET structures every data and AI project from first analysis to full handover. In each phase, you see who decides, what is delivered, and how your team is involved.
Three patterns we encounter in every other project.
Technology before strategy
Systems are built before the decision question is defined. The result works technically, but solves the wrong problem.
Data without a shared foundation
Sources are distributed and inconsistent. Analyses are built on numbers nobody in the organisation truly trusts.
Delivery without handover
Good solutions end as black boxes. When the external partner leaves, the knowledge goes with them and the system stalls.
What happens in each phase and what it means for your team.
Select a phase to see its goal, result, timeline, and team benefit.
Assess
Understand before acting.
Goal
Precisely capture the decision question and data reality, without technology assumptions.
Result
Situation analysis, goal definition and data reality assessment
Timeline
Week 1
For your team
After this phase, your team knows which data actually drives decisions and where time has been lost.
Scientific foundation
ADET follows the core CRISP-DM principles for structured data projects.
For AI projects, we extend with CRISP-ML(Q) practices such as monitoring and quality criteria.
We select methods based on your use case, never based on tools or vendors.
Clear roles, fixed cadence, transparent decisions.
To avoid projects getting stuck in handoffs, we define collaboration explicitly from day one, including decision logic, review cadence, and sign-off criteria.
Kickoff with decision-makers
Project startWe: We facilitate target state, KPI logic, and scope in a clear decision framework.
You: You prioritise business goals and assign functional ownership.
→ Aligned project roadmap with clear responsibilities.
Weekly delivery reviews
WeeklyWe: We provide transparent progress, risks, and upcoming decisions.
You: You give feedback based on real intermediate outcomes, not assumptions.
→ Fast corrections without costly rework loops.
Joint quality sign-off
Per phaseWe: We validate quality, reproducibility, and operability against clear criteria.
You: Your team validates business logic and decision usability.
→ Sign-off based on explicit criteria, not subjective judgement.
Enablement and handover
Closeout + transitionWe: We hand over documentation, runbooks, and training in a structured format.
You: Your team takes over operations and further development.
→ Independent operation without permanent external dependency.
What we build so your team can run it independently.
No vendor lock-in, no licence fees that grow with usage. What we build runs in your infrastructure and stays under your control.
Operating model in practice
We deliver in a way your team can run and extend the system long-term.
In your infrastructure
Cloud or on-prem: we deliver where compliance and operations fit your setup.
Open instead of proprietary
Open-source-first with standard interfaces instead of vendor dogma.
Operationally documented
Runbooks, tests, and clear ownership so your team can run it day to day.
Data Ingestion & Integration
Automated pipelines from all relevant sources: stable, monitored, internally operable.
Modeling & Transformation
Versioned, tested data models: reproducible and extensible.
BI & Visualisation
Dashboards that can be operated and extended internally, without proprietary dependency.
ML & AI / MLOps
Production models with monitoring, versioning, and retraining logic.
Governance & Quality
Data quality rules, lineage documentation and auditable decision logic.
Operations, Security & APIs
Systems run stable, role-based, and privacy-compliant in your infrastructure.
Enablement & Training
Your team takes full ownership: documented, trained, and empowered.
How would ADET apply to your specific project?
In 30 minutes we assess your data situation together and identify which phase delivers the biggest leverage.