One question, multiple systems
Answering a single cross-system business question shouldn't require manually reconciling three or more systems that don't talk to each other.
Putting data and AI to work across your organisation.

Data and AI is Avocado’s practice for turning data into measurable business outcomes. We work across three connected areas: data foundations that give your AI something trustworthy to work with, AI engineering that predicts, generates and acts, and adoption and governance that get your people using AI safely and confidently.
Our approach is technology-agnostic. We work across Azure, AWS, GCP, Databricks and Snowflake, and the current generation of large language models, including Claude, ChatGPT, Gemini, Grok and Copilot. Every engagement is built for your organisation rather than shoehorned into a template, and measured by the return it delivers, not just the technology deployed.
Answering a single cross-system business question shouldn't require manually reconciling three or more systems that don't talk to each other.
Generative AI pilots stall when the underlying data isn't governed or trustworthy enough to put in front of customers, staff or regulators.
Competitors are moving from AI that answers questions to AI that completes tasks. Without a governed data foundation, you can't safely make that shift.
AI governance and security expectations from regulators, boards and customers are rising faster than most internal policies.
A chatbot here, a dashboard there. Each one solves a single problem, but none of them builds on the last, so value stays trapped instead of growing over time.
Most organisations move through four levels of maturity: understanding what happened, understanding what’s happening now, predicting what’s next, and, where it’s safe and valuable, letting AI act autonomously on your behalf. Not every organisation needs to reach level four, and most shouldn’t attempt it without the earlier levels in place. A strong data foundation, such as a lakehouse, makes every level after it faster and cheaper to reach, which is why we assess where you actually are before recommending where to go.
Governed data platforms, dashboards and reporting that tell you with confidence what happened.
Extend that foundation to real-time and streaming data — video, voice, image — so you know what's happening right now, not just yesterday.
Apply machine learning, from supervised models through to reinforcement learning, to forecast what's likely to happen next.
Where it's safe and valuable, let agentic AI act on your behalf — completing tasks, not just producing answers.
Most AI initiatives stall between pilot and production. Our staged approach proves value early, so you only make the big investment once the evidence is there.
Define the problem, the expected uplift and the budget available.
Understand your data, test the make-or-break assumptions, and confirm cost, feasibility and return.
Build a small, auditable model that shows the outcome can be achieved, without heavy pipeline work.
Production pipelines, drift monitoring, integration into the systems that act on the outputs, and MLOps to keep models performing.
Typical share of investment. Ranges vary by project.
The governed data layer every AI initiative builds on.
A governed, production-ready data foundation, deployed in as little as 5 days.
Define your business terms and metrics once, so every AI tool and report gives consistent, trusted answers.
Move data out of spreadsheets, legacy systems and old warehouses, cleaned and fixed before it lands in its new home.
Reporting and single sources of truth that show what's happening across the business.
Access, quality, lineage and privacy controls that keep your data trusted and compliant, whether it feeds a report or an AI model.
Models and agents that predict, generate and act.
Predictive analytics that tell you what's likely to happen next, and why.
Content, chat and reasoning, tuned to your business.
AI that acts on your behalf, not just answers.
Video, images and signals turned into automated decisions.
Put AI to work on your IT operations, with faster detection, root cause analysis and remediation.
AIOpsTeams fluent in AI, with the guardrails to use it safely.
Microsoft Copilot, ChatGPT and Claude training for individuals and teams. AI upskilling that sticks.
Aligned to ISO/IEC 42001, NIST AI RMF and Australia's Guidance for AI Adoption.
Testing that AI models and agents give accurate, consistent and safe outputs before go-live, and keep doing so as they change.
Quality EngineeringProtection against AI-specific threats, including prompt injection, jailbreaks, data leakage through AI outputs and unauthorised agent actions.
Cyber and Operational ResilienceMonitoring of performance, cost, accuracy and agent behaviour once AI is live, so issues are caught before they reach customers.
ObservabilityBegin with an AI Strategy Workshop
A 1–3 day workshop that maps your opportunities and builds a prioritised roadmap before you commit to a strategy, budget and plan. Already know the idea, just not whether it stacks up? See the AI Readiness and Feasibility Study.
Deep specialisation across data, AI, ML and IoT — paired with the business and communication skills to translate it into outcomes executives actually care about.
Technology-agnostic by design — Azure, AWS, Google Cloud, Databricks and Snowflake, and the current generation of LLMs including Claude, ChatGPT, Gemini, Grok and Copilot.
Every recommendation weighed against the return it delivers, not just the technology behind it.
Custom-built for your organisation rather than shoehorned into a template.
A staged path from strategy to production, so you prove value before the big investment.
Governance built in — aligned to ISO 42001, NIST AI RMF and Australia's Guidance for AI Adoption.
An economics consultancy wanted AI productivity without exposing client data. We built a secure, custom AI platform with governance and the firm’s workflows built in.
Read the case studyAn Australian manufacturer had outgrown its legacy Access database. We moved its data into a cloud lakehouse with front-end apps and system integrations, creating one reliable source of truth.
Read the case study
Where it's safe and valuable, agents complete multi-step tasks using real tools — not just produce answers.
Read the case studyEverything from foundational data platforms and governance through to predictive machine learning, generative AI, and autonomous agentic AI — treated as one connected practice rather than separate technology silos.
Yes. If you need capacity or capability inside your own team rather than a fixed-scope engagement, our Project Delivery covers data engineers, data scientists, machine learning engineers, forward deployed engineers and other Data and AI specialists on a resource-augmentation basis.
AI is only as reliable as the data underneath it — a governed Lakehouse, and for AI specifically an AI-ready data layer, is a strong foundation. Smaller point solutions can take a less structured approach to reach a result quickly, while keeping the bigger picture in mind.
Generative AI produces an answer or a piece of content in response to a prompt. Agentic AI plans and completes a multi-step task using real tools, adapting as it goes. See the Agentic AI page for the full comparison.
It depends on scope — a Lakehouse foundation is a fixed 5-day build, while strategy, governance and agentic engagements are scoped individually. Most organisations start with a short workshop before committing to a build.
The AI Strategy Workshop is the standard entry point: a short workshop that maps your opportunities and gives you a prioritised roadmap before you commit to any specific build.
Why your AI needs a data lakehouse
How a governed data foundation makes every AI initiative faster and cheaper.Agentic AI vs Generative AI
What's the difference, and why does it matter?AI Readiness and Feasibility Study
Know whether you're ready, and whether it will work, before you commit.AI Leadership and Governance Workshop
Get your leaders aligned and your governance in place.Ready to talk about your Data and AI strategy?
Book a consultation, or start with an AI Strategy Workshop to map your opportunities first.