Your data is scattered across tools.
None of it talks to each other.

A proper data platform, without hiring a data team. End-to-end: ingestion to dashboards. Two phases: audit first, then a fixed-price build. Senior engineering, clean handover.

Let's talk

What brings most clients here.

The problem:

  • Spreadsheets are your reporting layer. They break.
  • Manual reporting eats hours or days before every board meeting.
  • Teams disagree on numbers. Same metric, different answers.
  • One person is the bottleneck. Every data question routes through them.
  • Basic questions take an afternoon. Hours of file-digging to answer.
  • Decisions get made on gut feel. The numbers aren't trusted.
  • Everyone's talking about AI, but you don't know if your data can support it.

What you get:

  • Dashboards your team trusts and opens every morning.
  • Reports that run automatically and email themselves.
  • One definition per metric: revenue, churn, LTV.
  • Self-service analytics, no ticket needed.
  • Decisions grounded in data, not gut feel.
  • Docs good enough for your next hire to take over.
  • AI features configured for natural-language queries over trusted data.

We build the platform, we hand you the keys, and we leave, with a 30-day support window so your team lands cleanly.

What we build, end to end.

Each layer chosen based on your data volume, team skill, and budget — not on which vendor pays partner commissions.

Three layers. All three done right.

Automated Data Pipelines

We connect your data sources (databases, APIs, SaaS tools) using Airbyte or Fivetran, depending on your needs. Data lands in BigQuery on a reliable schedule, with monitoring and alerts when something breaks.

Data Architecture & Modeling

Raw data is cleaned, modeled, and documented in Dataform or dbt. Staging, transformation, and reporting layers. Data quality tests built in from the start so issues surface before they hit dashboards.

Dashboards, Reports & AI-ready

We connect the BI tool that fits your team (Looker, Lightdash, Metabase, or Steep) and build the dashboards that matter. We also configure the AI features on top, so conversational analytics or AI agents query governed metrics, not raw tables.

The tools we reach for.

Every implementation uses some combination of these. The mix depends on your data sources, team, and budget. We explain the tradeoffs before we pick.

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 →

How an implementation runs.

Audit (1–2 weeks, €3,000 – €5,000)

Sources, volumes, and tools evaluated. Written recommendation and fixed-price build proposal. Available standalone.

Your decision (no pressure, no fees for deciding)

Proceed with the build, do it yourselves, or stop here. Plenty of clients take the report and execute internally.

Build (6–10 weeks, bi-weekly demos)

We lead the technical work. Your team joins reviews and decisions, and can take on small parts when it makes sense. Bi-weekly demos, async by default.

Handover (1–2 weeks)

Training sessions, full documentation, recorded walkthroughs. Your team owns it when we leave. Not in theory, in practice.

Post-launch support (30 days, included)

You have questions, small tweaks, an unexpected edge case. We're reachable for 30 days after handover at no extra cost.

Pricing.

Phase 1: Audit
€3,000 – €5,000

1–2 weeks, fixed price, paid 100% upfront. Written recommendation and fixed-price build proposal. Same audit available standalone.

Phase 2: Build (optional)
€12,000 – €30,000

7–12 weeks (build + handover), priced after the audit based on the real scope. Fixed price, agreed before we start.

Total range when clients do both phases: €15,000 – €35,000.

What affects the price

Factor Lower price Higher price
Number of data sources 2–3 simple sources 6–10 mixed sources
Transformation complexity Standard model Complex business logic
BI tool Steep / Metabase Lightdash / Looker with LookML
Orchestration needs None needed Dagster-based workflow

Example scenarios

Example: 3 sources, Metabase
€15,000 – €18,000
8–10 weeks

Startup with Postgres, Stripe, and HubSpot. Metabase for dashboards.

Example: 6+ sources, Looker
€25,000 – €35,000
10–14 weeks

Scale-up with product databases, marketing APIs, and finance tools. Looker with LookML.

Example: Shopify + ads, Lightdash
€20,000 – €25,000
8–10 weeks

E-commerce business with Shopify, advertising platforms (Meta, Google), and finance tools. Lightdash for the ops team.

Payment

Audit 100% at audit kickoff. Build 50% at start · 30% at the mid-project milestone · 20% on final handover. Fixed price. No change orders without a signed amendment.

Not sure this is the right fit?

Platform exists but not working?

Audit what you have, then build the improvements. Two phases: audit first, then a fixed-price build.

See Optimization

Scope is narrower than a full build?

Focused help on one or two layers: Dataform, Looker, BigQuery costs. Fixed-price, 2–6 weeks.

See Expert Services

Already have a working platform?

Monthly retainer for monitoring, incident response, improvements, and a senior engineer on call.

See Ongoing Support