Custom AI models, generative AI features and RAG pipelines for Melbourne businesses, built by engineers who ship production software, with Privacy Act 1988-aware data practices from the first sprint.
Built for production
Models · RAG · GenAI · Automation
From AI concept to real-world product.
An AI development company in Melbourne builds custom models, generative AI features, RAG pipelines and AI chatbots that plug directly into your existing product and data. A focused AI feature typically costs $25,000–$70,000 AUD equivalent, with a working MVP usually ready in 6-10 weeks. Delivery works the same way whether your team is in the CBD or across greater Melbourne, with Privacy Act 1988-aware data practices built in from the first sprint.
An AI model is only as trustworthy as the data pipeline feeding it. Every engagement starts with the same security baseline.
Security controls built into the AI development lifecycle.
Encryption at rest and in transit for all training and inference data
Role-based access control scoped to the smallest team that needs it
Independent code review before any model reaches production
From intelligent automation to production-ready AI systems, we build practical solutions around your product, data and business goals.
Explore the AI capabilities we can bring into your product, workflow or existing technology stack.
AI-Powered Hunting & Fishing Companion
Outdoor enthusiasts needed AI-assisted species identification and trip planning.
A real AI species-ID feature shipped to iOS users.
AI Content & Brand Approval Platform
Brands needed an AI-assisted review workflow for coordinating content across teams.
A working content-approval dashboard used by real creator and brand teams.
AI Photo & Avatar Generator
A consumer AI photography platform needed to turn a few selfies into professional-quality portraits.
Shipped at consumer scale with generative AI at the core.
The AI-powered fitness platform Apptechies developed integrates personalized workout plans, nutrition tracking, and real-time progress monitoring in one beautiful app. Their technical execution has been exceptional.
The MSK performance platform Apptechies built has changed how our clinicians track patient outcomes. The data-driven insights have significantly improved rehabilitation decisions, and the team understood our clinical domain deeply from day one.
Fraud detection and underwriting models built with real risk data.
Responsible AI engineering built around Australian privacy, security and governance expectations.
A model that ignores data-protection requirements isn't production-ready. It's a liability waiting to surface.
Privacy Act 1988 (Cth) and the 13 Australian Privacy Principles scoped into the architecture.
Notifiable Data Breaches scheme awareness for eligible data breach obligations.
Security practices aligned with the ACSC Essential Eight cybersecurity framework.
Bias testing and explainability documentation for every production model.
We combine engineering depth, product thinking and practical AI delivery to turn complex ideas into systems that can operate in production.
We build models that survive contact with real production traffic, not just a notebook demo.
Strategy, architecture, build and deployment handled by one team.
A real bench of engineers, designers and strategists.
Bias testing and explainability considerations scoped into the architecture from day one.
Recognised by real clients. Trusted by 500+ clients across 25+ industries.
Real tools our engineers use in production, selected around the requirements of each AI system.
We select models, frameworks and infrastructure based on performance, scalability and your product requirements.
Model choice depends on your data, latency, security and production requirements.
Identifying the single highest-leverage AI use case first.
Assessing what data exists and what needs cleaning.
Hosted API, fine-tuned model, or a grounded RAG pipeline.
A working prototype against real data within the first sprints.
Wiring the model into your product with rate limits and validation.
Accuracy and bias testing, then containerised deployment with drift monitoring.
The questions we hear most from teams hiring a ai development in melbourne. Don't see yours? Ask us directly on the right.
Custom models, generative AI features, RAG pipelines, AI chatbots and process-automation tools, matched to your product's actual data and workflow.
A focused AI feature typically runs $25,000–$70,000 AUD equivalent. A full generative AI product with multiple integrations can run $150,000+ AUD equivalent. We scope against your actual requirements after a discovery call.
We scope the Privacy Act 1988 (Cth) and the 13 Australian Privacy Principles into the architecture during discovery, including Notifiable Data Breaches scheme obligations, and align security practices with the ACSC Essential Eight framework.
We don't have an Australian office today. Our teams work from London, UK, Austin, Texas, and Mohali, India, and our Mohali team provides morning-hours overlap with Melbourne business hours.
Yes, we typically wire in a hosted model behind a RAG pipeline grounded in your own documents, so answers stay accurate to your business rather than generic.
A focused MVP typically takes 6-10 weeks. A full generative AI product with multiple integrations usually runs 16-24 weeks.
Yes, we're happy to sign an NDA before any detailed discussion of your data, business logic or systems.
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