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What We Do

Complex data problems, solved properly

Five areas where enterprises most often need senior help. We work across all of them, and we are direct when a problem is not ours to take.

Our expertise

01

Data Quality & Reliability

The data a business runs on has to be right, and it has to be right on a Monday morning without anyone checking by hand. We put testing, monitoring and incident response around the pipelines and tables that matter, and we make the results visible to the people who depend on them.

  • Data testing and contract enforcement
  • Freshness, volume and schema monitoring
  • Incident response and root-cause analysis
  • Reconciliation between systems of record
02

Data & AI Readiness

Most AI initiatives do not stall on the model. They stall on the data underneath it: undocumented definitions, no lineage, and no way to tell whether a training set is representative. We do the groundwork that makes an AI programme buildable, and we are direct about what is not ready yet.

  • Readiness assessment against a concrete use case
  • Lineage and documentation for the data in scope
  • Access, ownership and sensitivity mapping
  • Feature and training data pipelines
03

Data Migration

Legacy system migrations and cloud warehouse adoption, delivered without losing trust in the numbers along the way. The hard part is rarely moving the data. It is proving, to people who will be held accountable for the figures, that what came out matches what went in.

  • Target architecture and migration sequencing
  • Parallel running and reconciliation
  • Model rebuild in the new platform
  • Cutover, decommissioning and handover
04

Analytics & Decision Support

Analytics is worth what the decisions it changes are worth. We work backwards from the decision: what is being decided, by whom, on what cadence, and what evidence would actually move it. Then we build the smallest thing that answers it well.

  • Decision mapping and metric definition
  • Semantic and reporting layers
  • Experimentation and causal analysis
  • Self-serve analytics that teams genuinely use
05

Data Management

Ownership, definitions, master data and lineage that survive contact with reality. Governance fails when it is written for an audit rather than for the people doing the work, so we design it to be the path of least resistance.

  • Ownership and stewardship models
  • Business glossary and metric definitions
  • Master and reference data management
  • Lineage, cataloguing and access control

The Semantic Model

Senior expertise, backed by a dedicated team

You are not buying an individual, and you are not buying a pyramid. You get a senior counterpart who owns the problem, and a team behind them with the capacity to execute it.

  • We understand the problem first, in business terms, before proposing anything.
  • We define the approach and put it in writing: the outcome, the sequence, and how we will know it worked.
  • We bring together the right specialists for that specific problem rather than staffing whoever is free.
  • We deliver remotely, inside your tools and your rituals, shipping in increments you can review.
  • We stay accountable for the outcome. One team, one counterpart, from the first call onwards.

Technology

We have the technical depth to execute

Tools follow the problem, not the other way round. This is the stack we build in most often.

  • Snowflake
  • Databricks
  • Amazon Redshift
  • PostgreSQL
  • MongoDB
  • Elasticsearch
  • dbt
  • Apache Airflow
  • Apache Spark
  • Apache Kafka
  • Python
  • PyTorch
  • Looker
  • Power BI
  • Tableau
  • Metabase
  • AWS
  • GCP
  • Azure
  • Docker
  • Terraform
  • GitHub

Selected Work

What engagements look like in practice

We do not publish client case studies. The work sits inside systems and commercial decisions our clients would rather not see described on a website, and we would rather keep it that way.

What we will do is walk you through comparable engagements on a call: the context, what was actually wrong, how we approached it, and what changed by the end. Where a client is happy to be referenced, we will introduce you.

Ask us about relevant work

The shape of an engagement

A free advisory conversation, then a focused diagnosis where the problem warrants one, then delivery scoped to a written outcome. Project-based or an ongoing retainer, depending on whether the problem has an end.

Have a data problem you're trying to solve?

Let's talk about it.