Data you can trust, ready when you need it.
We build reliable data pipelines, warehouses and dashboards so your team stops arguing about numbers and starts acting on them. The same foundation makes your data ready for AI.
Sound familiar?
The signs it's time to bring us in.
Every team reports a different number for the same metric.
Reports take days of manual exports and spreadsheet work.
Pipelines break quietly and someone finds out a week later.
You want to use AI but your data is scattered across a dozen tools.
What you get
Concrete deliverables, not slideware.
Modern data platform
A warehouse or lakehouse sized to your volume and budget.
ELT pipelines
Reliable ingestion from your product database, SaaS tools and event streams.
Data modeling
Tested, documented dbt models with one shared definition for every metric.
BI & dashboards
Self-serve dashboards in Looker, Metabase, Power BI or your tool of choice.
Data quality & observability
Freshness, volume and schema checks that alert someone before a report breaks.
AI-ready data
Vector stores, embeddings and feature pipelines that power AI use cases.
How it works
A clear path, with results every step.
You'll always know what we're working on, what's next and how we're measuring success.
Week 1
Assess
Sources, questions the business needs answered, current pain points.
Week 2
Design
Architecture, tooling and metric definitions agreed with stakeholders.
Weeks 3–6
Build
Pipelines, models and the first high-value dashboards.
Ongoing
Expand
More sources, self-serve analytics and AI use cases.
Outcomes
What changes for you.
- One agreed number for every metric
- Reports that update automatically
- Faster, better-informed decisions
- A foundation for AI and machine learning
FAQ
Data Engineering & Analytics: common questions
Which warehouse should we use?
It depends on your volume, team and existing cloud. We'll recommend the simplest option that will scale. Sometimes that's just Postgres.
Can you work with our existing setup?
Yes. We often improve and stabilize existing pipelines rather than starting over.
Real-time or batch?
Batch covers most analytics needs and costs much less. We add streaming where the business case calls for it.
Related services
Often paired with.
AI Transformation
Find the highest-return AI use cases and ship them to production.
Learn moreWorkflow Automation
Automate repetitive work across your tools, with AI where judgment is needed.
Learn moreCloud, DevOps & Cost Optimization
Faster infrastructure, safer deploys and a smaller cloud bill.
Learn moreReady to talk Data Engineering & Analytics?
Tell us where you are and where you need to be. You'll get a straight answer on whether we can help, and how.
30 minutes · no pitch deck · no obligation