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AI Infrastructure · Service 11

Before you implement AI, somebody has to know where your data lives and who actually owns it. Usually, nobody does.

Most AI projects don't die because of the model. They die because data lives in six silos with no owner, no permissions and no governance. That base is what we put in order — and leave running.

We map where every piece of data lives, who controls it and who should be able to use it. We define ownership, permissions and governance. We don't hand you a risk report: we leave the data governance built, documented and operational — the foundation any AI can actually run on.

Promise: We don't audit your data and send you off to fix it alone. We leave it ordered, governed and running.

The product

This is what you get in your inbox.

AI Infrastructure

4 services · 99.97% uptime 90d

Requests / day

48.2k

+12% MoM

Cost / 1k tokens

€0.04

-23% optimized

P95 latency

312ms

target < 500ms

Services in production

Vector DB

12ms

OK

Embeddings API

48ms

OK

LLM Gateway

186ms

OK

Cache Redis

3ms

OK

Sound familiar?

You think you need an AI agent. What you have is six silos of orphan data.

AI pilots turn into zombies because data lives in scattered places, with permissions set by accident and nobody holding the keys. AI cannot run on a foundation that does not exist.

  • When you ask "where is X customer's data?" you get three different answers.
  • Every department keeps their own Excel/Notion/Airtable because "the official system doesn't work right".
  • Joiners and leavers leave access dangling for months — and nobody audits.
  • When a customer files a "right to be forgotten" request, legal panics because they have no idea where the trail lives.
  • You've paid for an AI pilot that works in demo and falls over in production because the model "doesn't understand the real data".

How we ship it

We put the data foundation in order in 8-12 weeks — and leave it alive

We don't hand you a PDF with recommendations. We implement the governance: catalog, lineage, permissions, runbook. When we leave, your team can maintain it without us and any AI project after that starts from a real base.

  1. Operational diagnosis (2-3 weeks)

    Interviews with the heads of every area, inventory of sources and permissions, flow map. Deliverable: a document with the current mess + a prioritized plan.

  2. Data catalog + lineage

    We deploy a catalog (DataHub, OpenMetadata or equivalent for your stack) with metadata, glossary and automatic lineage. Your team sees the full map for the first time.

  3. Role-based access policy

    We define what role can touch what data. We implement automatic revocations on joiners/leavers. Continuous audit switched on.

  4. Runbook + handover

    Operational document for your team: how to add a source, how to revoke permissions, how to investigate an incident. 1-2 training sessions so it stays in-house.

The classic data consultancy hands you an audit and walks out. We leave governance built, running and maintainable by your team — the phase 0 any AI can actually live on.

Honest filter

Is this for you?

We don't sell to everyone. Here's who it works for and who it doesn't — so you can decide with criteria before signing.

It's for you if…

  • Mid-market or enterprise companies that have already tried to implement AI and hit the data wall.
  • CTOs / CIOs / Heads of Data who need the foundation before stacking AI on top.
  • Regulated companies (banking, health, insurance) where data governance is not optional.
  • Organizations with 5+ systems/SaaS where the same data lives in several places.

It's not for you if…

  • Startups under 50 people with a single stack — you don't have this problem yet.
  • Companies that just want "a PowerPoint with the data strategy" — not our thing.
  • Anyone looking for outsourced DPO or a compliance auditor — that's a different (complementary) provider.

The concrete delivery

What exactly do you get?

What you receive when the service ships. No "discovery phases" billed separately, no "iterations" without scope.

  • Full inventory of data sources with owner, criticality and current permissions
  • Flow map: who consumes what, where it duplicates, where it breaks
  • Live data catalog (with metadata, glossary and lineage) deployed in your stack
  • Role-based access policy + automatic revocations implemented
  • Operational runbook so your team maintains governance without us

The promise: We don't audit your data and send you off to fix it alone. We leave it ordered, governed and running.

No surprises

What happens when you book a conversation

Here's what happens from signing day. Zero weeks lost in theoretical discovery.

  1. Day 1

    Kickoff with area heads

    A 90-minute meeting with the heads of each area that holds relevant data. We identify contacts and start interviews.

  2. Week 1-3

    Operational diagnosis delivered

    Full inventory + flow map + prioritized plan. Review with you and a decision: we stop here (you keep the plan to execute internally) or we continue with the full project.

  3. Week 4-8

    Catalog + lineage + permissions implemented

    Technical work in your stack. Validation with each area as their data enters the catalog. Access policy rolled out.

  4. Week 9-12

    Runbook + training + handover

    Operational documentation, 1-2 training sessions with your team, final adjustments. We leave with governance running and your people able to maintain it.

Pricing

How is this service quoted?

Due to technical complexity and integration, 30 minutes of conversation beats a cold quote.

Mid-market / enterprise

$1,500–$12,000

setup / project

Diagnosis from €1,500 · Full governance project from €12,000

Frequently asked questions

That's exactly the typical scenario. We map each SaaS as a source, identify overlaps (the same customer with three different IDs) and define the system of record for each entity. The catalog unifies the view; connectors already exist for 80% of common SaaS.

No. It complements it. Our focus is operational (knowing where every piece of data is and who touches it) and technical (catalog, lineage, permissions). Legal compliance is your DPO or legal counsel's job — but our governance gives them the material base they need to answer a request.

Diagnosis: 2-3 weeks. Full governance project: 8-12 weeks, depending on number of sources (5-15 systems) and starting maturity.

No. The most common case is that you DON'T have a formal data team — which is exactly why nobody has ordered the silos. We work with the head of each area (Ops, Sales, Product) who actually knows their data.

It's the natural flow. Once governance is in place, our AI Workforce and Enterprise AI Infrastructure services slot in directly — and they go in without the classic problem of the agent that doesn't know which source to query.

Move to a conversation?

Tell us what your situation looks like. If it fits what we do, we put a concrete proposal in front of you in 1 week.

Data Governance · Implementa