Reliable numbers to run your business.

We build, fix and maintain your data models and dashboards on BigQuery, dbt and Looker. Sales, margin, revenue, retention: one definition per number, traced back to source. Remote, in writing, at a fixed scope and price.

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The problem

Three teams, three revenue numbers, all of them "correct".

Finance excludes refunds, sales counts signed-not-invoiced, the exec dashboard sums something in between. It is not a tooling problem: it is a set of definitions that nobody wrote down and no model enforces. Neuravoid writes them, builds the model that applies them, and keeps it alive, in dbt, BigQuery and Looker.

One specialty, not a catalogue

Analytics engineering on Google Cloud: BigQuery, dbt, Looker, LookML. Your source systems can be anything, Shopify, Stripe, HubSpot, NetSuite, an ERP; the modelling is where the value is.

A quote within 24 hours

You describe your context, you get a scope, a timeline and a quote within one business day. No surprises after that.

Everything in writing

Written brief, delivery as reviewed, versioned code with a short explainer video. No calls, no staffing, no meetings: it is what makes a fixed scope at a fixed price possible.

Who it is for

Three businesses, one promise: numbers you can run on.

The same method, applied to the three reporting problems we see most: margin by channel for brands that sell everywhere, revenue and retention for SaaS, consolidated sales and margin for distributors with several branches. Each starts with a fixed-price diagnostic.

For e-commerce brands

E-commerce margin by channel

DTC, Amazon, Target, Walmart, Costco: one set of cost rules on every order, return and retailer deduction, and a weekly margin review that ties to the P&L.

See how it works

For B2B SaaS

SaaS revenue and retention

One MRR, reconciled to billing, CRM and product usage, with definitions of new, expansion, contraction and churn that finance, sales and product all signed.

See how it works

For B2B distributors

Distributor sales and margin by branch

Several branches, an acquisition, two ERPs: a weekly sales and margin review that consolidates them under one set of rules, without the Monday spreadsheet.

See how it works

Offers

Five offers, one stack: BigQuery, dbt, Looker.

Start with the audit if you already run Looker or dbt. With the build if your numbers contradict each other, with or without Looker. With the migration if you want to get to Looker. Upkeep takes over once the foundation is sound. Every offer has a scope, a timeline and a price; the quote confirms them within one business day.

Looker and dbt audit

Five days to go through your LookML project, your dbt project on BigQuery, or both: prioritised report and fixes delivered on a branch.

Timeline 5 business daysFrom $4,500 excl. VAT

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Fixed-scope BigQuery, dbt and Looker stack

Your data modelled, tested and documented: one definition per metric, ready for BI and for AI agents. 4 to 6 week engagement.

Timeline 4 to 6 weeksFrom $15,000 excl. VAT

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Migration to Looker

From Looker Studio, Power BI or Tableau: we model in dbt on BigQuery and in LookML what deserves it, re-point the dashboards that matter, train the analysts. 4 to 8 week engagement.

Timeline 4 to 8 weeks

See details

Agentic analytics pilot

Conversational Analytics, Looker MCP, agents wired to your semantic layer: a 4-week pilot so your teams can question data in plain language and get correct answers.

Timeline 4 weeks

See details

Analytics engineering retainer

Three days a month of a remote analytics engineer: LookML and dbt changes, review of your PRs, new models and explores, analyst training. Cancel any month.

Timeline 3 days / monthFrom $3,500 / month excl. VAT

See details

Reference implementations

Code you can read before you write to us.

Three complete, public stacks built the way we build them for clients: dbt on BigQuery, LookML, dashboard, linter and continuous integration. One per sector.

E-commerce

Margin, average order value, repeat rate, one revenue number. Public thelook_ecommerce dataset, 13 metrics, 3 explores.

View repository Read the guide

Healthcare

30-day readmissions, length of stay, chronic conditions, patient field protection. Synthetic Medicare data in OMOP format, 17 metrics.

View repository Read the guide

Fintech

Payment volume, chargebacks, churn, loan book and delinquency. Generated synthetic data, customer history, 56 metrics, 134 tests.

View repository Read the guide

How we work

In writing, as reviewed code, on video.

  1. 01

    You write

    Three lines on your systems (Shopify, Stripe, HubSpot, an ERP, BigQuery, dbt, Looker or the tool you want to leave), what is broken and the deadline. Answer within one business day with a scope and a price.

  2. 02

    We scope in writing

    Structured brief, access, list of deliverables, acceptance criteria. Questions answered in writing within one business day.

  3. 03

    Neuravoid delivers

    Code delivered separately (dbt, LookML), written report, explainer video. You review, then integrate.

  4. 04

    You decide what is next

    Retainer, next offer, or nothing. No commitment beyond the offer you bought.

Frequently asked questions

What people ask before signing.

Why only Google Cloud, BigQuery, dbt and Looker?

Because it is what Neuravoid runs in production and the only scope where a result in five days can be guaranteed. Your source systems can be anything, Shopify, Amazon, Stripe, HubSpot, NetSuite, an ERP: they are loaded into BigQuery, and the modelling is where the value is. Snowflake, Databricks and Power BI are not sold here.

We do not have Looker, only BigQuery and Metabase / Looker Studio: is this for us?

Yes. The value is in the dbt modelling on BigQuery and in the semantic layer, not in the BI tool. We build the models and the definitions, then your tool (Metabase, Looker Studio or another) connects to them. Migration to Looker is only suggested when it is relevant for you.

We are not on BigQuery at all. Is this for us?

Yes, if your systems export data: Shopify, Amazon, Stripe, HubSpot, NetSuite, QuickBooks, ERP exports. Loading them into BigQuery is part of the quote, with a managed connector or native exports. The reliability diagnostic works from exports, before any pipeline exists.

Do you work on site?

No. Everything is delivered remotely and asynchronously. That is what makes fixed scopes and short timelines possible.

Do you work with US and UK companies?

Yes, and the English site is priced for them: fixed prices in US dollars, delivered remotely. Evening availability in Europe overlaps with US East Coast afternoons, so written answers land in your business day. Invoicing comes from a French company, without VAT for clients outside the EU.

Can you work on a day rate or as staff augmentation?

The analytics engineering retainer replaces staffing: three days a month, remote, no required presence. For one-off needs, the fixed-scope offers cover most cases.

What about broader data engineering, generative AI, automation?

Analytics engineering on Google Cloud (BigQuery, dbt, Looker) is the job. Source ingestion (Fivetran, Airbyte, native exports) is scoped with you, not operated. Generative AI outside analytics, automation, other warehouses: out of scope, we say so honestly and point you elsewhere.

How fast can you start?

A Looker and dbt audit usually starts within ten business days. Longer engagements are scheduled at the brief.

Describe your context.

Your systems, the number you do not trust, the deadline. Three lines are enough. Written answer within one business day.

Write to Neuravoid

Or directly by email

contact@neuravoid.io