Before you build,
know what you're building.

A 1–2 week paid engagement to evaluate tools against your real data and requirements, and produce a fixed-price proposal for what comes next. Yours to keep, or Phase 1 of a larger build with us.

Let's talk

What brings most clients here.

The questions:

  • How many sources do we actually have, and how big are they?
  • What will our data stack cost us over 12 months, fees and infrastructure included?
  • Which tools do we actually need, and which can we skip?
  • Which BI tool will our team actually use?
  • Can our team maintain this day-to-day?
  • Vendor sales calls all sound the same. Which tools actually fit our case?
  • We want to add AI features but don't know if our data is ready.

What the audit answers:

  • Sources inventoried, volumes measured, current usage reviewed.
  • A 12-month total cost of ownership, fees plus infrastructure.
  • A tool recommendation matched to your data, team, and budget.
  • A target architecture, with reasoning you can challenge.
  • A written deliverable you own, even if you don't continue with us.
  • A fixed-price proposal for what comes next.
  • Whether your data is ready for conversational analytics and AI agents.

What you walk away with.

Current state assessment

Sources, volumes, current stack, current costs, current BI usage, and the gaps between where you are and where you need to be.

Target state recommendation

A proposed architecture and tool selection, with the reasoning behind each pick. Includes the semantic layer design that makes AI features accurate.

12-month cost estimate

A total cost of ownership over a year: Nimzo fees plus ongoing infrastructure. So you can plan, not guess.

Fixed-price proposal

A fixed-price build proposal as the final artifact, if you continue with us. Scope, timeline, and price. Ready to sign.

Want to see what the deliverable actually looks like?

See a sample audit

How an audit runs.

Kickoff & access

Kickoff call, read access to relevant systems, you nominate a point of contact.

Technical audit

Sources, volumes, pipelines, costs, and BI usage reviewed.
For clients starting from scratch: we audit requirements and data sources instead.

Tool evaluation

Tools matched to your situation: BigQuery, Dataform/dbt, Fivetran/Airbyte, Lightdash/Steep/Metabase/Looker. Demos where useful.

Findings & recommendation

Written deliverable: current state, target state, 12-month cost estimate, recommendation with reasoning.

Recommendation call & proposal

Walk through findings. Fixed-price proposal as final artifact, or just the recommendation if you don't continue with us.

Tools we evaluate against your situation.

We don't have a default stack. The audit matches tools to your data volume, team skill, and budget, with the reasoning written down so you can challenge it.

BigQuery
BigQuery Serverless data warehouse with built-in Gemini AI and EU data residency.
Dataform
Dataform SQL transformations built into BigQuery. Zero extra licensing. Our default.
dbt
dbt Industry-standard SQL transformations. Full support for your existing dbt projects.
Airbyte
Airbyte Managed ELT with 600+ connectors and a builder for custom APIs.
Fivetran
Fivetran Fully managed ELT with 600+ connectors and automated schema handling.
Looker
Looker Enterprise BI with LookML governance and Gemini conversational analytics.
Lightdash
Lightdash BI with metrics in code, dbt or native YAML. Flat-rate pricing, unlimited users.
Metabase
Metabase Approachable BI with dashboards, governed metrics, and Metabot AI.
Steep
Steep AI analytics built on governed metrics. Non-technical teams ask, get trusted answers.
Dagster
Dagster Asset-based orchestration. Declare pipelines and dependencies as code.

See all technologies and when we pick each →

Pricing.

Fixed price €3,000 – €5,000

1–2 weeks, paid 100% upfront at kickoff. Where you land in this range depends on the number of data sources and the complexity of your current setup.

Where this leads.

An audit is a real deliverable on its own, and it's also the natural Phase 1 of a larger engagement with us.

Starting from scratch

Data Platform Implementation

Full build from scratch. The audit produces the fixed-price proposal; you decide whether to proceed.

See Implementation
Improving what exists

Data Platform Optimization

Existing platform that isn't working. The audit identifies what needs improving and produces the fixed-price build proposal. No obligation to continue.

See Optimization

When this isn't the right fit.

  • You already know exactly what you want built and have a clear scope. Expert Services is a better fit: fixed-price, scoped in days.
  • You're not on GCP and not planning to be. We don't do multi-cloud. We're not the right partner.
  • You're pre-product-market-fit with no real data yet. Too early. Come back when there's something to measure.