Data infrastructure for the AI era
We prepare your data infrastructure for the AI era. From EU AI Act compliance to building first-party datasets for custom LLMs and predictive modeling.
- BigQuery
- Vertex AI
- dbt
- Claude API
- Snowflake Cortex
- OneTrust
✓ EU AI Act · first-party data · full-cycle delivery with Saloid
In short
We make your data infrastructure AI-ready, from EU AI Act classification of your use cases to first-party datasets for custom LLMs and predictive modeling. Compliance documentation from us, technical implementation together with Saloid.
- Who it's for
- Marketing, analytics & compliance with AI in the stack
- What you get
- Use-case risk register, first-party architecture & AI policy
- Entry
- Audit from €4,500, Build in 3 to 6 weeks
01Quick self-check
You're in the right place if:
Tick what applies.
02How it works
From inventory to governance, in four steps.
First know what's running, then classify, then secure the data foundation and the processes.
- Use-case inventory
Inventory
Capture every AI system in use, including the hidden ones like Smart Bidding, Advantage+, and HubSpot AI.
- EU AI Act risk matrix
Classify
Each use case is rated per EU AI Act, with a gap analysis of compliance against current state.
- BigQuery · dbt · OneTrust
Data foundation
Bring first-party data into an ML-ready schema, check the consent architecture, because AI only trains on consented data.
- Policy · human oversight
Governance
AI policy, human-oversight process, and documentation template, matched to each risk level.
03What we build
Was wir bauen
The EU AI Act applies in stages: prohibited practices since 2025, many central obligations from 2 August 2026, with further rules into 2027. Anyone using AI systems, including in marketing and analytics, needs use-case documentation, risk assessment, and in some cases human-oversight processes.
But AI Readiness is more than compliance. The question is: are your data and processes ready for the next step? Clean first-party data in a structured schema is the foundation for any AI use case that actually works, not just a GDPR checkbox.
Predictive audiences, AI-powered attribution modelling, LLM-based insight generation aren't future topics. They work today, but only at companies whose analytics foundation is in order.
Not legal advice: AI Readiness is data and infrastructure work. The legal assessment of your AI systems stays with your data-protection or legal counsel. We provide the technical foundation and the documentation it relies on.
04The difference
AI blind flight vs. documented AI readiness.
Not legal advice: the legal assessment stays with your data-protection or legal counsel. We provide the technical foundation and the documentation it relies on.
05The building blocks
Three pillars. One AI foundation.
Use-case assessment, data architecture, and governance, bookable individually or as a chain.
AI use case mapping & risk assessment
Which AI systems do you operate, knowingly and unknowingly? Many companies don't know how many AI components are already in their marketing tech stack.
Concretely: Inventory of all AI systems including hidden ones like Smart Bidding, Advantage+, HubSpot AI, risk assessment per EU AI Act per use case, gap analysis, and a prioritised action plan.
Tools: Custom Assessment Framework · EU AI Act checklists
First-party data architecture for AI
AI models are only as good as the data they run on. Fragmented data produces poor outputs, regardless of how good the model is.
Concretely: Audit of the data architecture for AI readiness, event-schema optimisation for ML inputs, consent-architecture check, recommendation for a data-lake setup if not in place.
Tools: BigQuery · Snowflake · dbt · OneTrust
AI governance & human oversight
Who decides what, and who reviews AI outputs before they inform decisions? These are process and organisational questions, not purely technical ones.
Concretely: AI policy document under applicable EU law, human-oversight process per risk level, AI literacy workshop (half-day), documentation template for EU AI Act compliance.
Tools: Custom policy templates · EU AI Act framework
06In plain terms
The key terms, briefly explained.
EU AI Act
The EU regulation for AI systems, in force in stages: prohibited practices since 2025, many central obligations from 2 August 2026, further rules into 2027.
First-party data
Data collected directly from your own users, with consent, on your own infrastructure. Available long-term and a more reliable foundation for AI models than third-party data.
Human oversight
A human must be able to review an AI decision and override it when needed. Often a documented review routine is enough, not a heavy process.
GPAI
General Purpose AI. Large language models (GPT, Claude, Gemini) used in internal tools or products fall under their own rules since August 2025.
07Who it is for
When it pays off.
Marketing teams using AI tools
Run AI-powered ad optimisation, GenAI content tools, or similar. As soon as AI tools process customer data, the EU AI Act applies.
Compliance leads
Need to assess whether company AI usage is compliant, and don't have internal resources to evaluate it rigorously.
Analytics teams
Want to lay the foundation for AI applications: first-party data architecture, structured event data, clean segmentation.
CTO / CDO in DACH
Know AI is coming and want to ensure the infrastructure is ready before pressure comes from above.
08Deliverables
What you end up with.
AI use case assessment
- Inventory of all deployed and planned AI systems
- Risk assessment per EU AI Act (which level, which obligations)
- Gap analysis: what's missing for compliance
- Prioritised action plan
First-party data readiness
- Audit of the data architecture for AI readiness
- Event-schema optimisation for ML inputs
- Consent-architecture check for AI training data
- Recommendation for a data-lake setup if not in place
AI governance
- AI policy document use-case-specific under applicable EU law
- Human-oversight process design per risk level
- AI literacy workshop for marketing and analytics teams
- Documentation template for EU AI Act compliance
What we do NOT do
Engagement depths
Three depths. Clear scopes.
No retainer trap.
Audit Sprint
We audit what is wrong. Prioritised report + action plan.
plus statutory VAT
Included
- Full analysis of the existing setup
- Prioritised report with concrete actions
- 90-minute walkthrough with your team
Not included
- Implementation (follows in the Build Sprint)
- Code in your app or website
When it fits
When the setup runs but the numbers are questioned internally.
Fixed price by scope (Audit Sprint / Audit Sprint Plus). 50% credited toward a Build Sprint if commissioned within 30 days.
Request an Audit Sprint →Build Sprint
Fresh build or restructure, built to spec.
plus statutory VAT
Included
- First-party data audit + BigQuery ML pilot
- EU AI Act gap analysis per use case
- AI readiness report + 12-month roadmap
Not included
- Campaign execution, media buying, creative
- Tool licences (billed directly, no markup)
When it fits
When a clean rebuild beats patching in production.
Final fixed price after scope definition.
Discuss a Build Sprint →Managed Evolution
Ongoing partnership. Analytics as a product.
plus statutory VAT
Included
- Monthly development + roadmap
- QA on every release deploy
- Slack support, < 4 h response (Mon–Fri)
- Monthly report + executive summary
Not included
- 24/7 on-call rotation
- Campaign operations
When it fits
When analytics has to keep growing with you.
Monthly cancellation after the minimum term.
Request Managed Evolution →All prices net, plus statutory VAT. For companies in Germany, Austria and Switzerland.
Does the EU AI Act apply to my company if we only use Google Ads Smart Bidding?
Yes. Smart Bidding is an AI system that makes bidding decisions. Under current guidance it doesn't fall into the high-risk category, but transparency obligations and internal documentation are still recommended. We clarify in the assessment exactly which use cases trigger which requirements.
What does human oversight mean in a marketing context?
When an AI system makes a decision, for example which segment sees which offer, a human has to be able to review that decision and override it when needed. The process doesn't have to be heavy; often a documented review routine is enough.
What is first-party data and why does it matter for AI?
First-party data is data you collect directly from your own users, with consent, on your own infrastructure. Unlike third-party data (cookies from outside providers), it's available long-term, usable under GDPR, and qualitatively more reliable. AI models trained on first-party data are more stable and produce better results than those trained on aggregated third-party data.
Which EU AI Act obligations apply, and when?
The Act applies in stages. Prohibited practices have been banned since February 2025, and General-Purpose-AI obligations since August 2025. Many central obligations become relevant from 2 August 2026, with further rules into 2027. Companies that move now avoid last-minute compliance pressure.
Next step
EU AI Act: where does your setup stand today?
Strategy call about compliance, first-party data, and custom-LLM foundations. Full-cycle implementation together with Saloid.
- Entry
- €4,500–9,500 net
- Delivery
- 3–6 weeks
- Scope
- 5 modules