How to Choose an AI Agency in Melbourne
Melbourne's tech scene has always been different from Sydney's. Less finance-dominated, more creative, stronger design culture. That matters when you're choosing an AI partner.
It also means the AI agency landscape here is... eclectic. Former digital marketing agencies, design studios, and software houses have all pivoted to "AI" in the past 18 months. Some did it well. Many didn't.
Here's how to tell the difference.
The Melbourne AI Market
A quick LinkedIn search shows 150+ agencies in Melbourne claiming AI capabilities. Let me break down what that actually means:
Genuine AI specialists (maybe 15-20 firms): Companies that were doing machine learning, NLP, or data science before GPT made it cool. They understand model architectures, training pipelines, and production deployment.
Software companies with AI capabilities (40-50 firms): Traditional dev shops that have added AI to their toolkit. Quality varies wildly. Some have invested seriously in upskilling. Others just wrap OpenAI's API and call it custom AI.
Rebadged agencies (the rest): Digital agencies, consultancies, and marketing firms that updated their website copy. "We now offer AI solutions!" Usually means they'll subcontract the actual work.
None of these categories is automatically good or bad. A software company with genuine AI investment might be exactly what you need. But you need to know what you're getting.
Questions That Reveal the Truth
"Walk me through a project that failed"
Every experienced AI team has failures. The technology is new enough that even experts get it wrong sometimes. If an agency claims 100% success, they're either lying or haven't done enough projects.
What you want to hear:
- Specific details about what went wrong
- What they learned from it
- How they've changed their approach
What's a red flag:
- "We've never had a failed project"
- Vague non-answers
- Blaming the client entirely
"Who specifically will work on my project?"
AI projects live or die based on individual expertise. You're not hiring a company, you're hiring people.
Ask to meet the actual team members—not just the sales person and a "technical advisor" who won't do the work. Ask about their backgrounds, their project experience, and their role in your engagement.
If they can't tell you who's doing the work, they probably don't know yet. Which means they're either under-resourced or planning to hire/subcontract.
"What happens after you deliver?"
AI systems aren't websites. You don't build them, launch them, and walk away. Models drift. APIs change. Edge cases emerge.
A good agency will talk about:
- Ongoing monitoring and maintenance
- How they'll handle model updates and improvements
- Knowledge transfer to your team
- Support SLAs and escalation paths
A concerning agency will:
- Focus only on the build phase
- Quote maintenance as an afterthought
- Not have clear answers about long-term ownership
"Can I talk to a reference who's been live for 12+ months?"
Demos are easy. Production is hard. Anyone can build a proof of concept that works in a controlled environment.
Ask for references from clients who've had AI systems running in production for at least a year. Ask those references about:
- How much ongoing support they need
- What issues emerged after launch
- Would they use this agency again?
Melbourne-Specific Factors
The university pipeline: Melbourne has strong AI research programs at Melbourne Uni, Monash, and RMIT. Some agencies have good relationships with these institutions for talent and research. That can be valuable—or it can mean your project becomes a training ground for junior researchers.
Industry concentration: Melbourne's economy has different weight than Sydney's. More retail, manufacturing, healthcare, education. Less financial services. Look for agencies with experience in your industry specifically.
The freelancer network: Melbourne has a deep pool of contract AI/ML engineers. Some agencies are really just coordinators assembling freelance teams. That's not necessarily bad, but you should know about it. Ask whether the team is full-time employees or contractors.
Remote-first realities: Post-2020, many Melbourne agencies operate hybrid or remote. This doesn't affect quality, but it does affect communication. Clarify how collaboration will work.
Red Flags Specific to the Current Market
"We'll use ChatGPT/Claude for that": Large language models are one tool. If an agency's answer to everything is an LLM wrapper, they have limited technical depth. Sometimes you need traditional ML. Sometimes you need rules engines. Sometimes you don't need AI at all.
Massive enterprise clients only: If every case study is a huge corporation, that might mean they're overbuilt for SMBs. Their processes, pricing, and timelines might not suit a mid-market company.
No case studies with measurable outcomes: "We built an AI chatbot for Company X" isn't a case study. "We reduced Company X's support costs by 40% over 12 months with an AI system" is. Demand specifics.
The "AI transformation" pitch: If they're leading with organisational transformation before understanding your specific problem, be cautious. Good AI projects start with specific use cases, not visions.
What Should It Cost?
Melbourne rates for quality AI work:
Discovery/Strategy engagement: $12,000-$35,000 for 3-5 weeks of scoping, data assessment, and roadmap development.
Proof of Concept: $25,000-$70,000 for a working prototype on real data, depending on complexity.
Production system: $80,000-$350,000+ depending on scope, integration complexity, and compliance requirements.
Ongoing support: $3,000-$15,000/month depending on the system's criticality and complexity.
Dramatically lower pricing usually means offshore development, junior teams, or scope that will blow out. Dramatically higher pricing might be appropriate for enterprise complexity, or might just be enterprise tax.
Our Position
We're Team 400. We started as a mobile app development company and moved into AI as clients' needs evolved. We're based in Sydney but work with Melbourne clients regularly—about 30% of our current projects.
We're not the right fit for everyone. If you need deep research ML—computer vision, custom model training from scratch—that's not our core strength. If you need AI integrated into production business systems, with a focus on practical outcomes rather than theoretical possibilities, that's what we do.
We built the AI scheduling system for Coast Smoke Alarms that saves them hours daily. We've deployed conversational AI that handles thousands of customer interactions monthly.
Happy to have a call about your situation—even if we end up recommending someone else.