Data Engineering & AI

Data platforms and pipelines — and the applied AI on top.

Overview

The data backbone and the intelligence on top of it: pipelines, warehousing and streaming that make data trustworthy, plus applied AI grounded in it — assistants, automation and decision support, cited, not theatre.

Where this fits

Your data is spread across systems, hard to trust, and the “AI” everyone keeps asking for only makes sense once the foundation underneath it is actually solid.

What you get

A data foundation you can actually trust

Answers grounded in your data and cited to source

Automation that removes real, measurable toil

What's included

Data pipelines, warehousing & lakehouse

Streaming & real-time data platforms

RAG assistants & applied AI

How we work

Our approach.

How the work actually runs on this — repeatable, visible, and owned end to end.

01

Make data trustworthy

Pipelines, warehousing and streaming so the numbers are correct, current and traceable to their source.

02

Ground the intelligence

Applied AI built on your own data — assistants and automation that cite sources instead of confidently making things up.

03

Prove the value

We target real, measurable toil and ship where AI earns its place — not for the headline.

Built with
PythonDatabricksMicrosoft FabricApache SparkAzure OpenAIRAG

The stack we reach for most on this kind of work — and we'll fit into your existing tools where it makes sense.

Start here

Let's take one hard thing off your plate.

A paid, time-boxed Technical Assessment of your product, systems or AI opportunity — ending with a concrete roadmap you own, whether or not you continue with us.