What this engagement includes
We reduce redundant copies of the same business entities across databases, files, and spreadsheets by making ingestion, modelling, and access explicit.
Work is sequenced with dependent initiatives (for example reporting or integrations); we flag prerequisites early.
How we deliver
We tailor and sequence these workstreams around your priorities, timeline, and internal constraints.
Modelling
Conceptual and physical models, keys, and slowly-changing strategies.
Ingestion
ELT/ETL, CDC, APIs, files - idempotent loads and data contracts.
Serving
Access patterns for apps, reverse ETL, and analyst tools.
Quality
Checks, alerting, lineage basics, and ownership metadata.
Our work
View our recent work below - each card links through to the live site.
We can walk through relevant case studies and references on a call - many of our clients ask for NDA-backed detail before we share specifics.
Typical flow
A reference sequence; we adapt depth and gates to your organisation.
- 01Inventory
Sources & consumers
Systems, SLAs, and today’s pain points with data.
- 02Blueprint
Architecture
Warehouse vs lakehouse, security zones, and cost guardrails.
- 03Build
Pipelines
Incremental delivery of domains (e.g. customers, orders).
- 04Govern
Operate
On-call expectations, change control, and roadmap for new sources.
| # | Stage | What happens |
|---|---|---|
| 01 | Inventory Sources & consumers | Systems, SLAs, and today’s pain points with data. |
| 02 | Blueprint Architecture | Warehouse vs lakehouse, security zones, and cost guardrails. |
| 03 | Build Pipelines | Incremental delivery of domains (e.g. customers, orders). |
| 04 | Govern Operate | On-call expectations, change control, and roadmap for new sources. |
Who we work with
Companies modernising data sprawl - from SMEs consolidating stacks to enterprises unifying divisions.
Infrastructure
We implement on AWS, Azure, GCP, Snowflake, Databricks, and self-managed stacks as your policies require.
Deliverables
Concrete outputs, documented and handed over with the build.
- Source analysis and modelling
- Pipelines batch or near-real-time as required
- Access patterns for apps and analysts
- Basic data quality checks
Engagement model
Partnership patterns we document in the SOW or master agreement.
- -Often paired with analytics or dashboard projects
- -Governance workshops with your data owner
Commercial model
Source count, latency requirements, governance, and consumption patterns set scope. We quote after discovery.
We start with a focused discovery (paid or unpaid, depending on complexity). You receive a written scope or SOW: milestones, acceptance tests, and a defined change process. NDAs and your procurement steps are routine.
Fixed scope
Documented requirements, milestones, and acceptance criteria. Delivery targets an agreed release or go-live.
When it applies
A bounded domain or source set with clear freshness and access rules.
Phased programme
Successive increments with checkpoints, integrations, and change control as scope evolves.
When it applies
Many pipelines, strict SLAs, or cross-functional data products.
Ongoing partnership
Retained monthly capacity for maintenance, incremental features, releases, and operational support.
When it applies
Operating pipelines, onboarding new sources, and quality remediation over time.
Fees are quoted per engagement after discovery. Third-party cloud, licensing, and usage charges are usually billed to your accounts unless we agree otherwise.
Talk to our team