What we run
Six instruments, one vessel
Each practice ships on its own, or as part of a longer voyage — most clients start with one and pull in the rest as the map fills in.
Data Engineering
Most data platforms don't fail loudly — they fail quietly, one broken job and one manual patch at a time, until nobody trusts the numbers. We rebuild the plumbing: idempotent ingestion, tested transformations, and orchestration your own engineers can read a year from now without a handoff call to us.
- Batch and streaming ingestion from source systems
- Warehouse and lakehouse architecture on your cloud of choice
- Orchestration, testing, and CI/CD for every pipeline we touch
- Cost and performance tuning for workloads already in production
Analytics & BI
A dashboard nobody opens is a maintenance cost with no return. We start from the decision, not the data model: what does the finance lead do differently on Monday morning, and what's the smallest report that changes that. Everything else is cut.
- Semantic and metrics layers with one definition of truth
- Executive, operational, and self-serve dashboard tiers
- Power BI, Tableau, and Looker implementation and migration
- Adoption support — training the people who'll actually use it
Applied AI
We scope AI work the way we'd scope any engineering project: a named task, a measurable baseline, and a rollback plan. That discipline is why the models we ship tend to still be running a year later, instead of quietly retired after the pilot.
- Use-case scoping and feasibility assessment before any build
- RAG, agentic, and classical ML systems grounded in your own data
- Evaluation harnesses that measure against your current baseline
- Production monitoring, guardrails, and cost controls
Data Governance
Governance that lives in a slide deck doesn't survive contact with a real audit. We encode ownership, access, and quality rules directly into the platform, so the answer to "who can see this and why" is a query, not a meeting.
- Column and table-level lineage across the full estate
- Role-based access control mapped to real business ownership
- Automated data-quality checks with alerting, not spreadsheets
- Documentation that stays in sync because it's generated, not written
Data Science
A model that lives in a notebook hasn't shipped. We pair the statistical work with the plumbing to put it in front of the person who has to act on it — a forecast in the planning tool, a segment in the campaign platform, a test result in the roadmap review.
- Demand forecasting and inventory optimization
- Customer segmentation and lifetime-value modelling
- A/B testing infrastructure and experiment design
- Statistical review of existing models before you scale them
Team Enablement
Every engagement ends with a handoff, and we treat that handoff as a deliverable in its own right — documentation, recorded walkthroughs, and paired sessions until your team can extend the platform without calling us first.
- Paired engineering sessions during the build, not just after
- Runbooks and architecture docs written for your next hire
- Workshops on the specific tools and patterns we implemented
- A defined off-ramp — no dependency on us to keep the lights on
Set a course
Not sure which instrument you need?
Most engagements start with a short scoping call, not a signed statement of work.