One source of truth across your stack.
Unified warehouse with ingestion, dbt modeling, governance, and monitoring. Clean, queryable, and trusted by finance, RevOps, and product. Shipped in 5 to 20 business days.
Every system, one warehouse.
Stripe, HubSpot, Postgres, Sheets. Whatever your team runs on, piped into a governed model your analysts and dashboards can trust. The packets on the right are your data, finally agreeing.
Stop reconciling spreadsheets at the end of every month.
Most companies don't have a data problem. They have a definitionproblem. Finance counts revenue one way, RevOps counts it another, and product analytics shows a third number. Every QBR turns into a debate about whose spreadsheet is right.
We pipe your tools into a clean, governed warehouse with one definition of every metric. Ingestion, modeling, semantic layer, and access control built on tools your engineering team already trusts. No fragile Looker model, no $200K consulting engagement, no eight-month rollout.
Every pipeline, model, and metric we ship is yours. Version-controlled in your GitHub, deployed to your warehouse, documented well enough that your analysts can extend it without us.
Everything you need in one engagement.
One flat fee, one team, one timeline. No per-row pricing, no surprise vendor sprawl.
Source audit and inventory
We map every system that holds data you care about, document the entities and update cadence, and rank what to wire in first.
Ingestion pipelines
Fivetran, Airbyte, or custom EL jobs depending on what fits. Incremental syncs, change data capture, and backfill handled correctly the first time.
Warehouse setup
Postgres, Supabase, BigQuery, Snowflake, or Redshift provisioned with sane defaults. Schemas, roles, and resource limits configured for your scale.
dbt modeling layer
Staging, intermediate, and mart models written in dbt with tests, documentation, and lineage graphs. Version-controlled in your GitHub.
Semantic and metrics layer
A single definition of revenue, churn, CAC, and the metrics that matter, queryable from BI tools, dashboards, or your LLM stack.
Governance and access control
Row-level security, column masking for PII, role-based access via Google or Okta SSO, and audit logs on every read and write.
Monitoring and freshness alerts
Pipeline failures, schema drifts, and stale-data warnings surface in Slack within minutes. No more dashboards quietly serving last week's numbers.
Documentation and handoff
Every source, model, and metric documented in plain English so your analysts and engineers can extend the stack without us.
Six data layers we ship every month.
If your team is rebuilding any of these in spreadsheets, we can replace the workflow in under three weeks.
Revenue source of truth
Stripe, HubSpot, and your billing system reconciled into one queryable revenue table. Finance and RevOps stop arguing about whose number is right.
Customer 360
Product events, support tickets, CRM activity, and billing history joined per account. Every team sees the same customer, with the same definitions.
Marketing attribution model
Ad spend, web events, CRM stages, and closed revenue stitched into a multi-touch model your CMO will actually defend in a board meeting.
Product analytics warehouse
Replace per-event vendor pricing with a warehouse-native stack. PostHog, Segment, or custom events landed in Postgres or BigQuery, modeled in dbt.
Operations data lake
Supply chain, fulfillment, support, and finance data unified for cross-functional reporting. No more month-end CSV exports passed by email.
AI-ready data layer
Clean, governed, embeddings-ready data piped into your RAG or agent stack. The unsexy work that makes LLM features actually trustworthy.
From source audit to live warehouse in one sprint.
No eight-month rollout. We work in daily increments and you see real, reconciled numbers within a week.
Source audit
30-minute working session. We map every source, every destination, and the decisions your team can't make today because the data is split.
Design and model
Warehouse choice, ingestion plan, and a draft semantic layer documented by day three. You approve the model before pipelines move.
Build and validate
Pipelines land data in staging, dbt models build the marts, and we reconcile against your source-of-record systems before going live.
Ship and document
Production cutover, monitoring wired in, full documentation, and a 30-day handoff window so your analysts can extend the stack confidently.
Built on the tools your engineering team already trusts.
No proprietary lock-in. Every pipeline and model is real code, deployable to your warehouse.
Scope your data integration in 24 hours.
Tell us the tools you need joined and the metrics you can't trust today. We'll send back a one-page scope with sources, model, governance, and a flat price. No sales call required.
- Reply within one business day
- Fixed scope and flat fee, no per-row pricing
- NDA on request, your data never leaves your warehouse
By submitting, you agree to be contacted about your request. We never share your data.
Questions teams ask before they hire us.
How long does a data integration project take?
Most single-source pipelines ship in 5 to 10 business days. Full multi-source warehouse builds with modeling and governance typically take 2 to 4 weeks end to end.
Which sources and destinations do you support?
HubSpot, Salesforce, Stripe, QuickBooks, Shopify, Intercom, Zendesk, Postgres, MySQL, MongoDB, Google Sheets, Airtable, Segment, and any REST or GraphQL API. Destinations include Postgres, Supabase, BigQuery, Snowflake, Redshift, and ClickHouse.
Do you use Fivetran, Airbyte, or build custom?
We use Fivetran or Airbyte when the connector exists and the economics make sense. We build custom EL pipelines when the source is bespoke, the volume justifies it, or you want to avoid per-row pricing.
How do you handle data modeling and transformations?
dbt for SQL transformations, version-controlled in Git with tests and documentation. Clean entities, stable IDs, sensible joins, and a semantic layer your BI tool or LLM can actually query.
What about governance, access control, and audit logs?
Row-level security at the warehouse layer, role-based access via your identity provider, column-level masking for PII, and full audit logs on every query. Compliance-ready from day one.
What does a data integration project cost?
Flat-fee engagements typically run between five and fifteen thousand dollars depending on source count, transformation complexity, and governance requirements. You get a written scope and fixed price before we start.
Got an idea? We can ship it next week.
30-minute discovery call. We tell you what's possible, what it costs, and when it ships.