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Pricing
Custom work, quoted after we talk.
Every client runs a different mix of platforms, accounts and reports, and most need custom work on top of the pipelines and dashboards. So we don't publish a price list. We learn your setup on a free 30-minute call, then send a written scope and a fixed quote.
What you get
No price list, and no surprises.
A fixed price, agreed first
A written scope and a fixed quote. Nothing is billed until you agree.
Start small
Most clients start with one platform and one dashboard, then grow.
You own what you pay for
Code, models, dashboards, docs and runbooks live in your repo and cloud.
How it works
From first call to a fixed quote.
First call
Bring your messiest report. We'll say what we'd fix first.
Written plan
What to connect first, what to build, what custom work makes sense, and a timeline.
Fixed quote
A price for that scope, agreed before any work starts. No surprises mid-build.
Build, then run or hand over
We build it, then run it monthly or hand it to your team with docs and runbooks.
What shapes the price
Four things decide the quote.
Platforms and sources
How many ad platforms, marketplaces and tools we connect, and how messy their APIs are.
Accounts and history
How many client accounts or brands, and how many years of history need backfilling.
Custom work
Bespoke metrics, client-specific views, data science, AI insights or agents beyond the standard model.
Who runs it
Whether we run it monthly, hand it over to your team, or embed engineers with you.
Ways to engage
Pick the model that fits.
Fixed-scope build
A defined build (pipelines, models, dashboards or custom data work) for a fixed price agreed before work starts. The scope is written down first, so you know exactly what the price covers.
Monthly run plan
We run what we built: watch the alerts, fix breaks when a platform changes, add reports and keep AI rules tuned. Agencies can white-label it.
Engineering pod
Senior engineers inside your repo, sprints and standups for SaaS and in-house data teams. Three-month minimum, then month to month.
White-label retainer
A defined monthly engineering capacity for agencies, priced so you can resell it to your clients under your brand.
Is it worth it?
Work out the hours you'd get back.
Move the numbers to match your team.
250hours back per month
$11,250of team time per month
$135,000per year
Mau Brands cut manual reporting time by 25% after we automated it. Use your own team's numbers. For a brand, try one or two people and the hours they spend on weekly reports.
Compared with
Your other options.
Hire a data engineer
One senior data engineer in the US costs $150k+ a year, and one person can't cover pipelines, warehouse models, dashboards and DevOps alone.
Connector tools
Supermetrics, Funnel and similar tools are great until you need a metric, platform or client view they don't support. That's usually where custom work starts.
TechEsthete
A senior team that has built this stack for Tinuiti, BTR Media, Pixis and SellerFuse, plus the custom work on top, in an account you own.
Pricing FAQ
Common questions.
Why don't you publish prices?
Because no two builds match. Four platforms across 60 client accounts with custom client views is a different job from one Amazon account and one dashboard. A 30-minute call gets you a real number instead of a guess.
What do we get before we commit?
A written scope with a fixed price. Nothing is billed until you agree to it.
Can we start small?
Yes. Most clients start with one platform and one dashboard, then add platforms, custom work and AI once the numbers are trusted.
Who owns what we pay for?
You do. Code, models, dashboards, docs and runbooks live in your repo and your cloud account.
What else will we pay for?
Your own cloud and warehouse usage, billed to you by your provider, and any BI licenses you choose. Looker Studio is free.
Get a quote for your setup.
Tell us your platforms, accounts and the custom work you need. A senior engineer replies within one business day.