AI Consulting
We're an AI consulting team for mid-market and enterprise leaders stuck between pilot purgatory and production. We get a real use case live in 8 to 16 weeks, with your team owning the system after we leave.
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The team behind your favourite AI Consulting
Get in touch →Trusted by the best for AI creative
Four lanes of real AI consulting, no theatre.
AI strategy and roadmap
We map the use cases that actually move revenue or cost, rank them by feasibility, and build a 12-month roadmap your board will sign.
Data readiness and architecture
We audit your data estate, fix the gaps that quietly kill models, and stand up pipelines on Snowflake, Databricks, or your existing warehouse.
Build, integration, and adoption
We ship the production workflow, wire it into your stack, and train your team to run it. Over 70% of pilots stall at integration. Ours don't.
Campaigns we’ve shipped.
Senior creative direction on every project.
From brief to first concepts.
Three packaged tiers, fixed scope and price.
AI Opportunity Audit — 2 weeks
A focused diagnostic across your workflows. You get a ranked use-case shortlist, ROI model, and 90-day plan. Ideal when leadership wants a defensible starting point.
Use-Case Sprint — 6 to 8 weeks
We pick one workflow and take it from proof of concept to production, including RAG, evaluations, and handover docs. The pattern we use for [commercial-grade visual systems applies to any production AI build.
AI Transformation Program — 6 to 12 months
A portfolio of three to six use cases delivered in parallel with a governance layer, an internal centre of excellence, and a clear exit plan so your team owns it. Related work: AI automation agency, AI keynote speakers, AI content creation, and our creative AI agency.
What clients say
“Came in with a rough deck, walked out with assets still running six months on. Same-day turnaround on every revision.”
“Got the brand on the first pass. Few rounds, no chase, no second-guessing.”
“A campaign a quarter became four, and the quality bar went up not down.”
Why teams pick us over the Big 4.
Builders, not deck-writers
Roughly 80% of every engagement is hands-on build. Our team writes the code, ships the integration, and stays in the room until it works in production.
Senior people on the actual work
The principal who scopes your engagement is in your Slack and your repo. No pyramid staffing, no junior handover. The same discipline shapes our [AI product photography in Brisbane work.
Governance built in from day one
We align to the NIST AI Risk Management Framework, EU AI Act readiness, and SOC 2 controls, so your legal and security teams clear the work without a six-month review.
From first call to production.
Diagnostic call
We spend 45 minutes on your stack, your data, and the workflow you want to change. You leave with a clear view of whether AI is the right answer.
Scoped engagement
We pick the right tier, lock the price, and start within two weeks. You get a named delivery lead and weekly working sessions, not status reports.
Handover and ownership
The system goes live, your team is trained, and the code, prompts, and runbooks are yours. We stay on a light retainer only if you want us to.
Absolutely AI vs. Traditional Studios
“We started Absolutely AI because brands were stuck choosing between slow studios and DIY tools. We wanted to give them a real creative team, just one that ships in days, not weeks.”
Common questions
What does AI consulting actually cost?
Our AI Opportunity Audit is a fixed fee in the low five figures. A Use-Case Sprint sits in the mid-five to low-six figure range depending on integration complexity. Transformation programs are quoted per use case so you only pay for what ships.
How long until we see something in production?
An audit delivers in 2 weeks. A sprint puts one workflow live in 6 to 8 weeks. The same delivery rigour that powers our [AI lifestyle photography work across Australia applies here: real outputs in days and weeks, not quarters.
Should we hire in-house or use a consultant?
Both, in that order. We get your first one or two use cases into production, document the patterns, then help you hire and onboard the internal team that takes it forward. Most clients have an internal lead by month six.
Build a custom system or buy an off-the-shelf tool?
Buy when the workflow is generic and the vendor has real traction. Build when the workflow is a competitive moat or your data is the differentiator. We will tell you to buy when buying is right, even though it earns us less.
Generative AI with LLMs, or traditional ML?
Depends on the problem. LLMs and RAG win for unstructured text, search, and agent workflows. Traditional ML still wins for forecasting, scoring, and anomaly detection. We pick the tool that fits, not the one that is trending.
Which models and platforms do you work with?
OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-weight models via Databricks or your own infrastructure. We use LangChain and standard MLOps tooling, and we design the architecture so you are not locked to one model provider. Related work: AI automation agency, AI keynote speakers, AI content creation, and our creative AI agency.
