Data Integration & Marketing Pipeline
We build the full pipeline — from your ad platforms and CRM into a clean, modeled foundation, and back out to the tools your team actually works in every day.
Context
A modern marketing data pipeline has four real stages, and most businesses only ever build the first two:
pulling raw data from your ad platforms, CRM, website, and product
getting it into a central place (a data warehouse) where it can actually be worked with
cleaning it, resolving duplicate identities, and modeling it into something useful (customer segments, lifetime value, propensity scores)
pushing that modeled data back out to your CRM and ad platforms, so your team actually uses it
Most businesses stop after "Extract" and "Load" — data sits in a warehouse or spreadsheet, technically collected but never actually acted on. The real value is in that last step: activation. Without it, you've built a very expensive filing cabinet.
Services
Context
A chatbot, CRM automation, or custom AI agent is only as good as the data feeding it. AI tools increasingly need real-time data access and clear data lineage to work reliably and safely — a pipeline that isn’t built for that will quietly limit everything built on top of it. This is why we treat data integration as foundational infrastructure, not a separate, optional add-on to your other AI work.
Our Process
Assess
Understanding your current data sources, tools, and where the gaps are.
Design
Choosing the right ingestion, transformation, and activation approach for your actual scale and needs.
Build
Connecting sources, setting up warehousing and modeling, and building activation back to your working tools.
Validate
Data quality checks and testing before anything goes live.
Monitor & Maintain
Ongoing monitoring so pipelines don't quietly break when a source platform changes.
Industries
Ecommerce & Retail
B2B & SaaS
Multi-Location & Franchise Businesses
Financial Services
Healthcare
Agencies & Marketing Teams
We build the whole loop, not just ingestion
Activation — getting data back out to where it’s used — is treated as core, not optional.
Right-sized architecture
Off-the-shelf tools where they fit, custom pipelines where they don’t — we won’t over-engineer a small business’s needs.
AI-ready by design
Real-time access and clear data lineage, since your other AI investments depend on it.
Built to keep working
Monitoring and maintenance so pipelines don’t silently break when a platform updates its API.
No long-term contracts
We keep earning your account every month.
Honest Timeline
Connecting a handful of core sources into a basic warehouse setup can typically be done in 3-5 weeks. A full pipeline including transformation, identity resolution, and activation back to your working tools typically takes 8-14 weeks, depending on the number of sources and complexity of the modeling needed. This is infrastructure — it needs ongoing monitoring after launch, not just an initial build.
Metrics
Pricing
Pricing depends on the number of data sources, complexity of modeling needed, and whether off-the-shelf tools or custom pipeline development fits best. We'll give you a clear estimate — including tool vs. custom-build recommendations — after a free data pipeline assessment.
Scoped to your project
Priced to the scope and complexity you actually need
Clear estimate upfront
A fixed-scope estimate after a free consultation
Honest recommendations
We recommend what fits, not the biggest package
Get a free data pipeline assessment — we'll show you exactly where the gaps are, and what's actually worth building.
FAQ
Free consultation
Share a few details and we'll get back to you within one business day.
We received your request and will reply within one business day.
