Common Questions, Straight Answers

We start every engagement with a discovery phase — understanding your business, data, and goals before proposing solutions. From there, we work in iterative sprints with regular demos, so you see progress and can steer direction. Most projects begin with a 2-4 week discovery, followed by phased delivery.

Discovery is a deep-dive into your business operations, data landscape, and strategic goals. We interview stakeholders, audit existing systems, and map out opportunities where AI can deliver the highest impact. The output is a prioritised roadmap with clear success metrics — not a generic proposal.

It depends on scope. A focused AI integration or chatbot deployment typically takes 2-3 months. A full product build (like Marvel PTE) can take 4-6 months. We always provide timeline estimates during discovery and work to predictable milestones.

Both. We've built products from scratch for startups and deployed AI solutions inside established enterprises. What matters to us isn't company size — it's whether there's a clear problem to solve and a commitment to acting on the results.

We focus on healthcare, education, retail, and professional services — industries where AI creates measurable operational improvements. Our case studies span patient scheduling systems, exam preparation platforms, business intelligence dashboards, and intelligent customer service.

Yes. We're happy to connect you with past clients for reference calls once we've had an initial conversation about your needs. You can also explore our case studies for detailed project outcomes.

We're framework-agnostic and choose the best tool for the job. Our stack commonly includes Python (PyTorch, TensorFlow, scikit-learn), large language model APIs (OpenAI, Anthropic, Google), cloud ML services (AWS SageMaker, Google Vertex AI), and custom fine-tuning pipelines. For web applications, we work across modern stacks including React, Next.js, and cloud-native architectures.

Absolutely. Most of our work involves integrating AI into existing business systems — CRMs, ERPs, data warehouses, and custom platforms. We design solutions that enhance your current stack, not replace it. Our integration approach ensures minimal disruption to ongoing operations.

Data security is non-negotiable. We follow industry best practices for data handling, support on-premise deployments where required, and are happy to sign NDAs before any discussion begins. All projects comply with relevant data protection regulations including the Australian Privacy Act.

Both, depending on the use case. For many applications, fine-tuned pre-trained models deliver excellent results faster and more cost-effectively. When a use case demands it — like our Marvel PTE scoring engine — we build custom models trained on domain-specific data. We always recommend the approach that delivers the best outcome for your budget.

Absolutely. We often start with a 2-4 week paid proof of concept to demonstrate value before committing to a full engagement. This lets you evaluate our approach, team, and results with minimal risk.

Every project starts with defined success metrics tied to business outcomes — not just model accuracy. We track KPIs like time saved, cost reduction, revenue impact, and user adoption, providing regular reporting against agreed benchmarks.

We offer both project-based fixed pricing and ongoing retainer arrangements. Every engagement starts with a scoped discovery phase so we can provide accurate pricing based on real requirements, not guesswork. We're transparent about costs and don't surprise you with hidden fees.

Yes. We offer maintenance and optimisation packages that include monitoring, model retraining, feature enhancements, and priority support. Most clients choose ongoing support because AI systems benefit from continuous improvement as more data becomes available.

Our headquarters are in Melbourne, Australia, but we work with clients globally. We've delivered projects across Australia, Southeast Asia, the Middle East, and Europe. Remote collaboration is part of our DNA — we use the same tools and processes regardless of location.

Absolutely. We understand that many AI projects involve sensitive business data and proprietary processes. We're happy to sign mutual NDAs before any detailed discussions begin. Just let us know and we'll have one ready.

Yes. Knowledge transfer is built into every engagement. We want your team to be self-sufficient, not dependent on us. This includes documentation, workshops, and hands-on training sessions.