Source integration
Connect product DBs, SaaS tools, analytics platforms, and files into a central warehouse or database.
Data Pipelines & ETL
Get your data into one reliable place.
We design and build data pipelines so product analytics, reports, and AI features run on consistent, well-modeled data instead of spreadsheets and exports.
Sources → warehouse → models
Built for analytics & AI usage later
What we design in data pipelines
Transformations & modeling
Clean, join, and model data into tables that reflect how your business actually works.
Quality & monitoring
Basic checks, alerts, and documentation so broken data doesn’t silently corrupt reports.
Data for AI features
Prepare the right views and embeddings-ready datasets that future AI features can plug into.
You'll benefit if…
- Teams build custom reports by copy-pasting from multiple tools.
- Numbers don't match between dashboards and your product.
- You want to add analytics/AI but data is scattered and messy.
Outcome after an engagement
- • A clear data architecture diagram
- • Working pipelines with monitoring
- • Modeled tables your team can analyse or build on
How we build your data pipelines
- 01Current state mapping
List data sources, consumers, and the reports or features that need them.
- 02Design & modeling
Define warehouse schema, key tables, and grain in a way your team understands.
- 03Implement & test
Build pipelines, run test loads, and compare numbers with existing reports.
- 04Docs & handoff
Document flows, ownership, and next steps for analytics or AI features.
Want data you can actually trust and use?
Share your tools and the reports you rely on. We'll outline a realistic data plan that supports both analytics and AI.