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Pipelines & ETL
dbt and Airbyte pipelines pulling every source — CRM, billing, ads, product, spreadsheets — on a schedule that just runs, with tests that catch bad data before it spreads.
Data engineering & AI analytics
Ask your data anything. Get answers, not dashboards nobody opens.
Your numbers are trapped across Stripe, Shopify, your CRM and fourteen spreadsheets. We build the pipelines, warehouse and natural-language layer that turn them into answers — typed in plain English, delivered in seconds, trusted because they're governed.
What we build
Six layers between you and the truth.
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Cloud warehouse
BigQuery or Snowflake, modeled into clean, documented tables. One governed source of truth instead of five conflicting exports.
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Executive dashboards
Power BI or Looker dashboards built around the five numbers leadership actually watches — designed to be opened daily, not screenshot once a quarter.
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Ask-your-data layer
"Which reps outsold their pipeline last month?" — typed in English, answered from governed models in seconds, with the SQL shown so it's checkable.
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Forecasting & alerts
Revenue pacing, churn risk, anomaly detection. The system taps you on the shoulder when a number moves — you stop refreshing dashboards to find out.
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Cleanup & single truth
Deduplication, currency and timezone normalization, definition alignment — so "revenue" finally means the same thing in every meeting.
Every build includes
Numbers you can argue from, not about.
- Data audit first — every source mapped, the vital few metrics identified before we build.
- Governed models — metric definitions live in code, so every report agrees with every other.
- Checkable AI answers — the NL layer shows its SQL and sources. Trust is verified, not asked for.
- Tested pipelines — data-quality tests and alerting, so bad data dies at the door.
- Your cloud, your keys — warehouse, code and dashboards in accounts you own.
- Documentation & walkthrough — recorded handover any data engineer could pick up.
Built on proven rails
The stack we ship in production.
- dbt
- BigQuery
- Snowflake
- Power BI
- Looker
- Airbyte
- Fivetran
- Postgres
- Python
- Claude
- GPT
- Metabase
- Tableau
- Supabase
- Segment
- Slack alerts
For most SMBs, BigQuery wins on cost and zero-ops simplicity; Snowflake earns its premium at heavier scale. The audit ends with that math done for your actual volumes — warehouses billed to your cloud account, never marked up.
How it ships
From scattered exports to answers in weeks.
Data audit
Every source mapped, the vital metrics defined, the warehouse choice made with real cost math.
Pipelines + warehouse
Core sources flowing into governed models, tested and documented. First real numbers in week two.
Dashboards
The executive view built around the numbers leadership watches daily — not a chart museum.
NL layer + alerts
Plain-English querying from the same governed models, plus anomaly alerts where your team lives.
From $15,000 — retainers available
Fixed-price scope signed before work starts. Warehouse and tooling typically run $150–$800/month at SMB scale, billed to your own cloud account — never marked up.
Proof, not promises
VantagePoint Capital — investment firm
Board reporting ate the first week of every month.
Analysts exported from five systems, reconciled in Excel and prayed the numbers matched. We built pipelines into BigQuery, governed dbt models and a natural-language layer — now the board pack drafts itself and partners query the portfolio in plain English.
6d→45mboard reporting
5systems unified
0Excel exports
45minfor what used to take six days
Questions
What buyers ask before trusting their data.
Our data is a mess across spreadsheets and tools — where do we start?
With a data audit: every source mapped, the one or two numbers that run the business identified, and pipelines built from those sources first. Most clients see a trustworthy first dashboard in two to three weeks.
BigQuery or Snowflake — how do we choose?
For most SMBs, BigQuery wins on cost and zero-ops simplicity. Snowflake earns its premium with heavy multi-team workloads. The decision comes out of the audit with real cost math — both billed to your own cloud account.
Do we still need dashboards if we can ask in plain English?
Yes — different moments. Dashboards for the numbers watched daily; the NL layer for every question that isn't. Both read from the same governed models, so ad-hoc answers never contradict the official dashboard.
What does it cost?
Foundations — pipelines from core tools plus one executive dashboard — start at $15,000 fixed-price. Full platforms with the NL layer run to $75,000. Warehousing is typically $150–$800/month at SMB scale, billed to your account.
Who owns the warehouse and pipelines?
You do — cloud account, warehouse, transformation code and dashboards, documented so any data engineer can take over. Retainers exist if you'd rather we run it, but leaving is always free.
Pairs well with
AI Agents & RAGNumbers answer half the questions — documents answer the rest. Cover both.Explore →
Vertical AI AutomationAlerts that act: when a metric moves, the workflow responds automatically.Explore →
Vibe-Code Rescue & MVPsBuilding a data product? We ship the app around the pipeline too.Explore →
Which number do you not trust right now?
Book a free 30-minute strategy call. Tell us the question your data should answer but can't — we'll map the pipeline and give you a fixed price to make it answer.