AI, data and analytics · GenAI Sprint
Find where generative AI fits your business in two days
A fixed-price sprint with our AI practice lead. You leave with your use cases ranked by value, effort and risk, a proof-of-concept scope and a roadmap to production, and you decide what to build from there.
What you leave with
- Prioritised use casesEvery idea from the workshop scored on value, effort, risk and data readiness
- Proof-of-concept scopeWhat gets built first, the data it needs, the success measure, and what it would cost
- Production roadmapFrom the proof of concept to a system your people rely on, with the governance steps in sequence
- Workshop board and summary packEverything captured, written up and sent within the week
- Fixed price, fixed scopeA$5,000 for two days. You know the cost before you book
- Run by our AI practice leadWith input from the engineers who would build the proof of concept
- Written outputsA ranked use-case list, a proof-of-concept scope and a roadmap
- Risk and privacy included in the scoringEach use case is checked against Australia's Guidance for AI Adoption
Who it is for
Two kinds of business book this sprint
Operators
You run a business with manual work in it
Typical examples are documents that staff read and re-key into another system, customer questions that are answered from the same small set of sources every day, and finance, HR or operations admin that a capable person does by hand. The sprint works out which of these generative AI can take on, what it would save, and what it would take to run it safely.
Software companies
You are adding AI to a product
Customers are asking for AI features and you need to decide what to build first. The sprint works through what the feature should do, which model and retrieval approach fit, what it will cost to run, and how you will test it before it reaches customers. Our engineers have put retrieval, agent and evaluation systems into production, and the scope is written with that experience.
Not for you if you already have a scoped use case and a budget; in that case skip the sprint and talk to us about the build. And if you are an SME in a National Reconstruction Fund priority sector, an AI Adopt Centre may give you a free readiness consultation first.
How it runs
Two consultant days, spread over about two weeks
Kick-off call
Forty-five minutes to align on goals, the problems you already know about, who attends and what we need to see beforehand.
Stakeholder interviews
Short one-to-one conversations across the teams involved, so the workshop starts from how the work is done today.
Workshop
A half day with your decision makers: ideas captured and scored, then a deep dive into the top candidates. Architecture, data, risks, success measures.
Write-up
The scored use cases, the proof-of-concept scope and the roadmap, written and sent within the week. A review call to walk through it.
Most of what we recommend runs on platforms you already pay for. For Microsoft 365 estates that is Copilot, Azure OpenAI and Azure AI Search; for Google Workspace it is Gemini and Vertex AI. Where an open model or a different vendor fits better, the roadmap says so and why.
Why now
Most Australian businesses are using AI. Few have a plan for it.
Most organisations are using AI in some form. Far fewer have decided which use case to build first, how to build it and how to measure whether it worked. The sprint answers those questions in two days.
Book the call
Choose a time
Tell Ben what prompted the search, for example a board question, a product roadmap decision or a process that takes up too much of a team's week. He will confirm the sprint is the right fit, agree dates and send an agenda. Ned runs the sprint itself.
You will have a written confirmation of scope, dates and the A$5,000 price the next business day.
- No sales pitch. If a sprint is not what you need, Ben will tell you on the call.
- Your details are used to set up the call and send the confirmation, nothing else.
Prefer email or phone? Send a note or call +61 2 7200 2554.
Who runs it
Who runs the sprint
The lead
AI practice lead
Ned leads our AI and machine learning practice: production AI systems, data engineering and applied machine learning delivery. He runs every sprint himself.
The engineers
Retrieval, agents, evaluation
Our engineering team builds retrieval-augmented systems, agents and the evaluation harnesses used to test them, on Azure, AWS and open models. The people who would build the proof of concept review the scope before you receive it.
The firm
Australian since 2010
Coder Trove has worked with mid-sized and enterprise organisations across Australia since 2010, across Dynamics 365, cloud, cyber security and custom software as well as AI.
Read how we think about this work: why AI projects fail on retrieval, why the evaluation harness matters more than the model, and a production AI system in invoice finance.
Common questions
GenAI Sprint questions, answered
What do we get for A$5,000?
Do we need clean data first?
Is this a Copilot readiness assessment?
What happens after the two days?
Who should attend?
Can you run it remotely?
Is generative AI regulated in Australia?
We are a small business. Is there a free alternative?
What happens to our information?
Related: AI, data and analytics practice · Permission-aware RAG
Start here
Book the first call
Thirty minutes with Ben, then a confirmed sprint date and a written scope the next business day.