Aurelia
AURELIA

Consulting practice

Eight practices.
One standard: production.

Every engagement ends in a running system with an owner, a metric, and a measured return — delivered with AIDLC discipline and powered by our own platforms.

01

AI Strategy & Readiness

For enterprises that need direction, prioritisation, and an execution-ready roadmap before committing more budget.

Value mapping, use-case prioritisation, and a roadmap with owners and measures — so AI investment stops spreading thin and starts compounding.

02

Agentic Systems & Automation

For enterprises ready to move beyond isolated copilots and automate cross-system workflows with governed agents.

Multi-agent systems built around your actual workflows — document processing, operations triage, orchestration — with human oversight and audit built in.

03

Custom ML & Data Engineering

For enterprises whose problems don't fit off-the-shelf models — and whose data pipelines aren't ready for the ones that do.

Domain-specific models on your proprietary data — tabular, time-series, NLP, vision — with the pipelines and feature platforms to keep them fed.

04

Model Fine-tuning & Evaluation

For enterprises whose domain has its own vocabulary, formats, and judgment calls that prompting can't reliably capture.

LoRA, DPO, RLHF, instruction tuning — foundation models tuned on your labeled data, delivering higher accuracy at a fraction of the inference cost.

05

AI-Native Modernization

For enterprises whose core systems still matter but slow down every integration, change, and AI initiative.

Legacy systems wrapped, mapped, and modernized with AI at the core — without betting the business on a big-bang rewrite.

06

Embedded AI Teams

For enterprises that need senior AI capability inside their organisation now — not a vendor on the other side of a ticket queue.

Aurelia engineers, data scientists, and domain specialists embedded in your teams — shipping with your stack, your rituals, and our discipline.

07

Forward Deployed Engineering

For enterprises that want outcomes delivered inside their walls — engineers who deploy, adapt, and ship on-site until the number moves.

FDEs embed with your operating teams, stand our platforms up against your live data in week one, and iterate in the field daily — measured on your outcome, not our deliverables.

08

AI Architects as a Service

For enterprises that need principal-level AI architecture — without the principal-level hire they can't find.

Fractional senior architects who own your AI reference architecture, chair your design reviews, make the build-vs-buy calls, and keep every vendor honest — including us.

The delivery system

Why our engagements ship.

Structured phases

Defined phases instead of ad-hoc experimentation — clearer decisions early, less drift later, a reliable path from strategy to execution.

Tangible deliverables

Roadmaps, scorecards, blueprints, running systems. The goal is not more discussion but work that moves the number.

Quality gates

Eval suites, sign-off criteria, and shadow deployments — AIDLC discipline on every engagement, so surprises surface early.

Measured outcomes

Every initiative carries an owner, a metric, and a kill criterion. ROI is tracked from day one, not reconstructed later.

Not sure which practice fits?

Most engagements start with a two-week strategy sprint that maps your data to the decisions it should be driving.

Book a strategy sprint