Practical AI · Built in Melbourne
Strategy that ships, not slides
Audits and roadmaps that come with working systems. The deliverable is the deck plus the deployed pipeline — never one without the other.
Why most AI strategy work ends in a deck
Strategy decks are easy to write. The hard part is what comes next — shipping the pilot, training the team, picking the right vendor, and making sure the audit findings turn into real operations. Three failures keep showing up when we read other agencies' strategy work.
Recommendations with no implementation cost.
Strategy decks list 'opportunities' without estimating effort, vendor risk, or time-to-pilot. The buyer is left with a wish list and no priority order.
Vendor recommendations untested in your context.
Generic 'use Tool X for Use Case Y' advice ignores your existing stack, your team's skill profile, and the integration cost. The advice is correct in the abstract and useless in practice.
Roadmaps that never become production code.
Most engagements end at the deck handover. Six months later, the document is in someone's drive and nothing has shipped. The audit work didn't pay back.
How we deliver it
Every engagement ends with code in production, not just a document. We start with a discovery audit — interviews with the operators, a walk-through of existing systems, and a documented inventory of the candidate use cases. The audit produces a roadmap that names each opportunity, estimates the build effort, and ranks them by ROI and time-to-ship. Then we build the highest-value pilot — typically one that can ship inside the same engagement window. Where the right answer is a vendor purchase rather than a custom build, we say so plainly and run the procurement comparison ourselves. Workshops with your team happen alongside the build, so by the time we leave, your operators understand the system well enough to extend it. The toolset is picked per project — Claude, n8n, LangGraph, or a custom Python service depending on what fits the use case. The deliverable is always the same: a documented roadmap plus at least one operation running in production.
Tools we lean on: Claude · n8n · LangGraph · Python — picked per project
Engagement shape · AI Strategy
- 01Audit
- 02Roadmap
- 03Workshop
- 04Build
- 05Ship
What an engagement covers, end to end
Six things every consulting engagement we ship includes by default.
Discovery audit.
Operator interviews, system walk-through, and a documented inventory of the candidate use cases. Two weeks of structured discovery before any roadmap is drafted.
Prioritised roadmap.
Each opportunity named, scoped, effort-estimated, and ranked by ROI and time-to-ship. Vendor recommendations come with the procurement comparison attached.
Working pilot.
Every engagement ships at least one operation in production — typically a pilot that runs through to a real outcome inside the engagement window. Code, not slides.
Team upskilling.
Workshops alongside the build mean your operators can extend and maintain the system after we leave. Documentation and runbooks land in your drive, not ours.
Measurement framework.
Each pilot ships with KPIs, baseline measurements, and a quarterly review template. The success of the engagement is measurable from week one.
Risk and governance review.
Privacy, data residency, model-risk, and vendor concentration assessed against your industry context. Findings land in the roadmap, not buried in an appendix.
Engagements start at three sizes
Most clients land on Scale. We re-quote against scope and pilot complexity after the discovery audit.
Automate
From $2,000 AUD
Targeted audit on a single use case. Five-page summary with effort estimate and vendor recommendation.
- Half-day discovery interview
- Single-use-case audit
- Effort and ROI estimate
- Recommendation memo
Scale
From $5,000 AUD
Full audit, prioritised roadmap, and one shipped pilot inside the engagement window.
- Discovery audit (2 weeks)
- Prioritised roadmap
- One shipped pilot in production
- Operator workshop
- Quarterly review template
Transform
From $10,000 AUD
Programme engagement — full audit, multi-pilot delivery, and 12-week implementation runway with team enablement.
- Full audit + roadmap
- 2-3 pilots shipped to production
- Team enablement workshops
- Vendor procurement support
- Quarterly programme reviews
Real-world scenario · 2025
Audit findings shipped in production within 8 weeks
A Sydney professional services firm asked us to audit where AI could pay back across their operations. The brief was specific: don't deliver a deck and disappear. They had been through two prior strategy engagements that produced documents and not much else.
The discovery audit ran for two weeks — interviews with seven operators across three teams, a walk-through of their existing stack, and a documented inventory of fourteen candidate use cases. The roadmap ranked them by ROI and time-to-pilot, naming three high-value automation candidates that could ship inside an eight-week engagement window. We built all three in parallel — a client-intake summariser, a research-citation assistant, and an internal knowledge search — using Claude, LangGraph, and a custom Python adapter for their CRM.
All three pilots shipped to production by week eight. The client-intake summariser was in everyday use by the close of the engagement, with measurable time savings. The other two went into staged rollout with a quarterly review template attached. Six months later the firm had absorbed the operations into their team without a follow-up engagement.
Read the full case studyTime from kickoff to production
Operations shipped end-to-end
Pilot in everyday use by close
Questions clients ask before they book the call
Why do you ship code as part of a strategy engagement?
Decks alone don't pay back. Most strategy work ends at the document handover, six months pass, and nothing ships. We bundle a working pilot into the engagement so the audit findings have a forcing function: by the close, at least one operation is in production. The roadmap and the deck still exist — they're the planning artefact, not the deliverable.
What if the right answer is buy, not build?
We say so. About a third of the use cases we audit turn out to be better served by an off-the-shelf vendor than a custom build. When that's the case, we run the procurement comparison ourselves — short-list, demos, scoring — and hand you a buy recommendation rather than building something redundant. The strategy engagement covers the procurement work; we don't have a 'build everything' bias.
Who owns the code after the engagement?
You do. All code, infrastructure config, and documentation lands in your repositories from day one. We don't lock anything behind a service contract. If you want us to maintain it post-engagement, we offer a separate retainer; if you'd rather extend it yourselves, the codebase plus runbooks are designed for that.
How do you measure whether the engagement worked?
Each pilot ships with KPIs and a baseline measurement taken before code goes live. The metrics are agreed upfront — typically time saved, error-rate reduction, or capacity reclaimed. Quarterly review templates live in your drive after we leave, so the operations team can keep measuring even without us. We expect to be hired back to extend what's working — not to defend what we built.
How long does a typical engagement take?
AI Strategy engagements on the Scale tier run 6-8 weeks from kickoff: 2 weeks discovery audit, 1 week roadmap, 4-5 weeks pilot build. Automate-tier engagements run 1-2 weeks. Transform-tier programme engagements typically run 12 weeks with multiple pilots in flight. Discovery is always front-loaded — nobody writes pilot code until the use cases are understood.
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