05  ·  DATA & CLOUD

The layer that makes everything above it trustworthy

Every AI system, dashboard and automation inherits the quality of the data underneath it. This is the practice that makes the rest defensible: pipelines that fail loudly, warehouses that agree with themselves, and infrastructure somebody other than us can operate.

Book a scoping callFree, and it ends with a range or a straight no.

What we build

Four areas, frequently sequenced as a single programme.

Data engineering

Ingestion and transformation with tests on the transformations, so a silently wrong number is caught before it reaches a decision.

Analytics and BI

Models and dashboards that answer the questions the business actually asks, with one agreed definition per metric.

Cloud migration

Incremental, reversible, with cost modelled before the move rather than discovered after it.

Security and compliance

Access control, encryption, retention and audit designed in at the schema level rather than retrofitted under deadline.

Observability is part of the deliverable

A pipeline without monitoring is a pipeline that will be wrong for weeks before anyone notices. Alerting and lineage ship with the work, not after it.

Shipped work

Not a portfolio of screenshots — every one of these opens.

  • Axiom

    Private research instrument

    A research workspace that turns a question into a defensible trail: it reads sources, separates claims from reasoning, and keeps the link between them. Reports stay in a private library with a source collection per project, and the workspace shows how much research context a report consumed.

    axiom-agent-three.vercel.app

What we build on

  • Snowflake
  • dbt
  • AWS

Halyx is not religious about the stack — it picks what your team can maintain — but these are the defaults it is fastest and safest in.

Questions we get asked first

Do we need a warehouse before we can do anything with AI?
Not always, and it is worth asking before committing to one. Some AI work runs perfectly well against operational systems; some is impossible without a warehouse. The assessment is short.
How do you handle data residency?
It is a design constraint from the first architecture conversation, not a compliance review at the end. Tell us the jurisdictions early.
Can you reduce our cloud bill?
Often, though the honest version is that the saving usually comes from changing what runs rather than from tuning what already does.

The other four practices

Talk to the people who would build it

The first conversation is a scoping call, not a pitch: what you are trying to move, what already exists, what the constraint is. It ends with either a range and a proposed first step, or a straight answer that Halyx is not the right fit.