AI strategy consulting that leads to working systems
ComplxAI provides AI strategy consulting for Australian organisations that need a plan they can execute, not a briefing on what AI might do. Each recommendation is checked against your data, your systems and a costed architecture by the engineers who would build it, and each gets a build, buy or defer call.
- Discovery and Strategy: 2–4 weeks each
- Two free conversations first
- The plan is yours, whoever builds
For leaders who need a decision, not a briefing
Owners, executives, product leaders and technology leaders bring us the same problem: the board wants a position on AI, product wants to know which ideas are real, and engineering wants the data checked first. Whether a written AI strategy came before the first build, or was written afterwards to explain it, is one of the questions our State of AI Development in Australia 2026 report asks.
If the use case is already clear, go straight to custom AI development. For one team across the whole path, first call to production, see AI consulting. This page covers the two planning stages.
A good fit if…
- You hold the budget and need a board-ready plan
- You lead product and have more AI ideas than evidence
- You lead technology and want feasibility checked before committing
What AI strategy consulting covers
Six pieces of work, each with a written finding.
Technical feasibility assessment
Data readiness, integration surface and model fit, examined by engineers: what data exists and how clean it is, which systems expose an API, and whether an LLM, a classical model or plain software fits.
Architecture options and cost modelling
Candidate architectures for each priority item: infrastructure sketch, model and token cost, licence costs where relevant, and the effort to build and run.
Build, buy or defer
Buy where a product already does the job, build where the workflow or data is yours, defer where the data or return is not there yet.
Governance and risk
Where data may travel, which model providers are acceptable, what you require to stay in Australia, where a human approval belongs and how privacy obligations shape the design.
Sequencing quick wins and platform work
Early wins that pay for the platform, and platform work that stops those wins becoming disconnected scripts. The first 12-week block is named.
Measurement plan
A baseline for each use case before anything is built, the metric it should move, and how quality is scored in production.
Two paid stages, two to four weeks each
Both sit inside the five-stage model in how we work, priced in writing first, with an exit at either boundary.
- Intro callFree, 30 minutes. Your goals and whether we fit.
- Pre-discoveryFree, one hour. A walk through your systems and data.
- Discovery2–4 weeks, from a fixed fee. Interviews, process mapping, data review. Output: a use-case map scored by impact, effort and risk.
- Strategy2–4 weeks, priced upfront. Feasibility, architecture, costs, governance, sequencing. Output: a board-ready plan with build, buy or defer calls.
- ImplementationOptional. 12-week blocks, working software every couple of weeks, by us or your team.
What we assess before recommending anything
A use case reaches the plan only when every layer has an answer. Where one fails, the item is deferred, with the reason.
- DatareadinessSources and ownersVolume and historyQuality and gapsPII and residency
- IntegrationsurfaceAPIs and webhooksDatabasesXero, MYOB, HubSpot, SalesforceDocument storesPermissions
- ModelfitLLM, classical model or rulesRetrieval needsAccuracy barLatencyCost of error
- Architectureand costServerless or containersOrchestrationVector searchToken and infrastructure cost
- Governanceand riskData boundariesPrivacy obligationsApproval stepsAudit trail
- MeasurementproofBaselineTarget metricEvaluation method
The same engineers ship the systems described under AI engineering and generative AI consulting, so findings rest on what we have built.
A strategy deck versus a ComplxAI plan
A conventional engagement ends with a document. Ours ends with a plan checked against your data and systems.
| Question | Strategy deck | ComplxAI plan |
|---|---|---|
| Feasibility validated by engineers | Assumed from desk research and vendor material. | Checked against your data and systems by the engineers who would build it, with a model-fit test where needed. |
| Architecture and cost model | A budget range. | Candidate architectures per item with infrastructure, model, licence and effort estimates. |
| Build, buy or defer per item | A recommendation to invest, by theme. | A specific call on every item, including those we advise against. |
| Sequencing | Phases on a timeline. | The first 12-week block defined in detail, then early wins funding platform work. |
| What happens next | A follow-on scoping engagement. | The first block is scoped; implementation follows, with us or another team. |
Four situations the plan is built for
A professional-services firm
Partners want AI for drafting and document review, but the knowledge sits in email, shared drives and people's heads. We establish what can be retrieved reliably, which confidentiality rules apply and what to automate first.
A SaaS company
The board wants an AI feature and product has a list. We test each candidate against the data the product holds, model token cost per tenant at scale, and rank them on the evidence customers will pay. Then AI product development takes over.
An operations-heavy business
Quoting, scheduling, invoicing and reconciliation run on spreadsheets, a finance system and staff who know the exceptions. We map those exceptions and decide where agentic workflow automation can act and where a person must approve.
A regulated business
Health, financial services or NDIS providers with data-residency requirements and decisions that must be explained. We fix data boundaries and approval steps first, then find use cases that fit. Systems are deployed in the region you need; for Australian data residency that is the AWS Sydney region.
What you walk away with
A scored use-case map, feasibility findings, costed architecture options, governance rules, a sequenced plan and a measurement baseline, in one document any team can start from.
Why take the plan from an engineering company
We build what we recommend
One small senior team does strategy, engineering and deployment, so we recommend only what we are prepared to build and run.
Independent on build versus buy
We are independent, with no mandatory retainers. A buy or defer call costs us a build. We make it anyway.
Same team, shipped systems
The systems in our case studies were scoped, architected and built by the same small team that writes your plan.
Where the plan leads
AI consulting
First call to production.
AI consulting in AustraliaAI development
The build items, delivered as software.
AI development servicesAI engineering
Retrieval, evaluation, observability, AWS.
Production AI engineeringAI product development
AI-native products and SaaS features.
AI SaaS product developmentGenerative AI consulting
Where LLMs fit and how to measure quality.
LLM consultingCan we run strategy without a build?
Yes. Discovery and Strategy are self-contained stages with their own price and deliverable. You can take the plan to an in-house team or another partner, with no obligation to continue.
Do you validate feasibility technically?
Yes, and it is the main difference from a conventional engagement. Engineers examine your data, integration points and candidate models, and where needed run a small model-fit test on a sample.
Will you recommend building more than we need?
No. Every item gets a build, buy or defer call, and defer is a real answer. Advising you to buy, or wait, costs us a build. We say it anyway.
Will the plan make sense to non-technical leadership?
Yes. The plan states each recommendation, its cost, expected return and risk in plain language, with the architecture and data findings behind it.
What does AI strategy cost?
Discovery starts from a fixed fee and Strategy is priced upfront, both in writing before work begins. The two conversations before them are free. For build cost ranges, the AI project cost calculator gives a rough figure.
Bring the question, not the answer
Tell us what the board is asking and what has been tried. The first two conversations are free; both paid stages are priced in writing first.