Four disciplines,
one line.
Engineer the data. Operate it like software. Learn from it. Turn it into revenue. Each stage compounds the one before it.
Data Engineering
Everything else stands on this. We build the pipelines, warehouses, and governance that make data a durable asset rather than a recurring emergency — designed so your team can run it without us.
Pipeline architecture
Batch and streaming ingestion that fails loudly, recovers gracefully, and documents itself.
Modern warehousing
Warehouse and lakehouse design with modelling that mirrors how your business actually thinks.
Data quality & governance
Contracts, tests, and lineage so every number on a dashboard can defend itself.
Migration & modernization
Moving legacy stacks to modern tooling without pausing the business that runs on them.
DataOps
The discipline that separates stacks that stall from stacks that compound. We run data like production software — every change tested, every dataset observed, every incident caught and healed before it reaches a decision.
Observability & SLAs
Freshness, volume, and schema monitoring with SLAs your business can actually see and hold us to.
CI/CD for data
Versioned transforms and automated tests on every change — dashboards stop breaking on Mondays.
Incident response & auto-healing
Retries, circuit breakers, and runbooks so failures resolve themselves — and page a human only when judgment is needed.
Cost & performance governance
Warehouse spend and query performance treated as first-class metrics, reviewed monthly.
Applied AI
Models deployed where they earn their keep — in production, measured against outcomes people actually care about. We favour the smallest system that solves the problem, and we always ship the evaluation alongside the model.
LLM applications
Retrieval, agents, and copilots grounded in your data — with guardrails and observability from day one.
Workflow automation
AI that removes the repetitive middle of a process while keeping people at the judgment points.
Custom & fine-tuned models
When off-the-shelf isn't enough: task-specific models trained on your domain.
Evaluation & safety
Eval suites and monitoring that tell you how the system behaves before your customers do.
Revenue Intelligence
The last mile, where most data investments quietly die — and where ours are scored. Forecasting, pricing, and attribution wired into live decisions, measured in the only unit that settles arguments: revenue.
Demand & revenue forecasting
Forecasts with honest uncertainty, scored against actuals every week — no cherry-picked backtests.
Pricing & promotion
Elasticity models and promotion optimization that protect margin while they grow volume.
Attribution & marketing ROI
Know which spend earns and which spend leaks — and reallocate with confidence.
Experimentation
A/B infrastructure and causal analysis so "it seems to work" becomes "it works, by this much."
Four steps, no mystery.
Discover
We map your data reality — sources, gaps, and the decisions that matter most — before proposing anything.
Design
A system design your team reviews and owns: architecture, milestones, and what "working" will mean.
Build
Short cycles, working software every week, and evaluation baked in from the first commit.
Operate & hand over
We run it with you, document everything, and leave when your team no longer needs us.
Pick the shape that fits.
Every engagement ends with something your team owns. The only question is how much we build together, and for how long.
Sprint
One expensive question, answered with evidence. An audit, a prototype, or a proof of value.
- Data & AI readiness audit
- DataOps health check
- Roadmap you can execute
Build
A production system, shipped end to end — pipeline, DataOps layer, model, or revenue system.
- Production deployment
- Documentation & training
- Evaluation suite included
Partner
A standing data & AI team beside yours — building, operating, and improving quarter over quarter.
- Dedicated capacity
- Quarterly revenue review
- Knowledge transfer built in
Tell us the number
you need to move.
We'll tell you honestly whether data and AI can move it — and what the smallest useful first step looks like.
Get in touch →