Your data platform exists.
It isn't working.
We audit what you have, tell you what's actually wrong, and implement a prioritized fix. Two phases — audit first, implementation second. Senior engineer on every project.
What brings most clients here.
The target. What your platform should look like.
Sources
Shopify 
Postgres 
Stripe 
Salesforce 
Meta Ads 
Google Ads 
HubSpot 
Amplitude Warehouse
Orchestration
You probably have some of these layers. Some are missing. Some exist but need replacing. The audit tells us which.
Three layers. Same three we fix.
Data Pipelines
Replace legacy Python scripts with Airbyte. Add monitoring and alerting that actually fire. Fix the three pipelines nobody touches because they scare everyone.
Data Architecture & Modeling
Refactor the models nobody understands. Cut BigQuery costs with partitioning, clustering, and query rewrites. Add tests so data quality issues stop reaching your dashboards.
Dashboards, Reports & AI-ready
Migrate off BI tools your team has given up on. Rebuild trust in the numbers by rebuilding the numbers. Set up the semantic layer so when you're ready for AI features, the foundation holds up.
The tools we work with — yours and ours.
We work with your existing stack first. If something needs replacing, we tell you why and what we'd use instead.
How an optimization runs.
Audit (1–2 weeks, €3,000 – €5,000)
We review your GCP architecture, query costs, pipeline reliability, and data quality. We interview your team. You get a written report and a prioritized fix list.
Your decision (no pressure, no fees for deciding)
Proceed with the implementation, do it yourselves, or stop here. The audit is valuable on its own — plenty of clients take the report and execute internally.
Implementation (6–10 weeks)
We implement the fixes from the audit — in the priority order you approved. Fixed price, agreed before we start.
Handover (1–2 weeks)
Training, documentation, recorded walkthroughs. Same as a greenfield build, just on the platform we improved.
Post-launch support (30 days, included)
30 days of reachability for questions, tweaks, edge cases.
Pricing.
1–2 weeks, fixed price. You get a written audit report and a prioritized fix list. You can stop here and execute internally — the audit fee is yours either way.
6–10 weeks, priced after the audit based on scope. If you proceed, the audit fee is credited toward the implementation.
Total range when clients do both phases: €20,000 – €50,000.
What affects the price
| Factor | Lower price | Higher price |
|---|---|---|
| Current state | Mostly working | Fundamentally broken |
| Technical debt | Isolated issues | Systemic across layers |
| Migration scope | Keep most tools | Replace legacy stack |
| BI tool migration | Stay on current tool | Migrate to new tool |
Example scenarios
Performance and cost optimization — schema redesign, query tuning.
Tool modernization — move legacy Python to Airbyte, add Dataform.
Major overhaul — multiple migrations, complex data quality issues.
Why is this more expensive than building from scratch?
Two reasons.
Investigation
We spend the first week of every optimization understanding what previous engineers built — decisions made by people who may no longer be at the company, working around constraints we didn't create.
Interconnection
Most broken platforms have connected problems. Fixing the slow dashboard means fixing the transformation model, which means fixing the pipeline that feeds it. We price to cover that investigation, not just the final fix.
Payment
Audit 100% at audit kickoff. Implementation 50% at start · 30% at the mid-project milestone · 20% on final handover. Fixed price. No change orders without a signed amendment.
Keeping it fixed.
An optimized platform needs less maintenance than a broken one, but it still needs some. Monthly retainers cover monitoring, small improvements, and a senior on call.
See retainer options →