Frequently Asked Questions

Yes. We can design and deploy applications so that data, application hosting and processing remain within Australian cloud regions or data centres. Hosting arrangements can be tailored to your data residency, security, compliance and regulatory requirements, including for government and other sensitive workloads.

Yes. We build applications that function seamlessly in low-connectivity and offline conditions, which is a critical requirement for clients operating across remote Australia, including heavy industry environments like the Pilbara.

No. Your data, code and intellectual property are never used to train AI models, ours or any third party's. Where we use AI tools during delivery, we use enterprise configurations that exclude client content from model training

We align security practices with the ASD Essential Eight and the Australian Government Information Security Manual (ISM) where applicable. Security is built into architecture, development, deployment and operations rather than treated as a final-stage checklist.

Yes. We support regulated organisations with secure architecture, access controls, resilience, disaster recovery, monitoring, incident response and technical documentation mapped to applicable APRA requirements, including CPS 230 and CPS 234.

We apply Privacy by Design principles, including data minimisation, appropriate consent mechanisms, access controls, encryption and retention practices. We design systems to collect only the information required for the intended purpose and protect it throughout its lifecycle.

Yes. Appinventiv is an approved ICT supplier to the Australian Digital Transformation Agency and is listed on Queensland Government ICT arrangements, including ICTSS.1303B and ICTSS.2403. We are also a pre-qualified Local Buy supplier.

Custom software development costs in Australia generally start from around AUD 70,000 to 150,000 for a focused first build, AUD 150,000–350,000 for mid-complexity platforms, and AUD 400,000–700,000+ for larger enterprise or regulated systems.

Government projects may sit towards the higher end because of additional security, residency, assurance and documentation requirements. These are indicative ranges; the final cost depends on scope, integrations, security, compliance and infrastructure requirements.

The major cost drivers that affect your final software development costs in Australia are:

• Feature scope and complexity, custom versus configured
• Design and user experience depth
• Number and complexity of integrations
• Security and compliance requirements
• Data residency and sovereignty constraints
• Offline or low-connectivity requirements
• Platform footprint, e.g. web only versus web plus iOS and Android

There is no single price range that fits every project. The actual app development cost in Australia varies depending on multiple variables. Typically, a future ready mobile app development costs in Australia fall between the following ranges:

• MVP Development: AUD 70,000 to 150,000
• Mid Complex Project: AUD 150,000 to 300,000
• Advanced Project: AUD 300,000 to 500,000
• Enterprise Grade Project: AUD 500,000 to 700,000 and above

It depends heavily on the type of AI work, so the range is wide. A retrieval-based assistant is a very different cost to a custom model or a production agent. The main drivers are your data quality, use-case complexity, guardrail and integration needs, and the governance to run it safely. Data prep and ongoing operation often cost more than the build, so we scope AI individually and usually start with a contained first AI use case in Australia.

On average, AI development costs range between AUD 70,000 and AUD 700,000 or more.

The most effective cost reductions come from decisions like:

• Phase the build and expand on real usage.
• Separate must-haves from nice-to-haves before committing.
• Reuse and integrate rather than rebuilding what works.
• Configure where a proven platform fits; reserve custom for differentiators.
• Invest in clear requirements upfront to avoid rework.

Spending a little more on discovery early usually lowers total development cost.

You must budget for app maintenance from the start. While there is no pre-defined range of app maintenance cost, as a general rule of thumb, it runs around 15 to 20% of the build cost per year, though it varies. It covers security patching, dependency and platform updates, monitoring, minor improvements and support, not just bug fixes. We size it against your roadmap and SLA needs rather than applying a flat percentage.

We offer all three engagement models: fixed price, time and materials, and dedicated team. Fixed price suits well-defined scopes; time and materials works better when requirements may evolve; and dedicated teams suit longer-term programmes requiring continuity and capacity.

The project timeline in Australia scales with complexity: a focused first release around 3 to 4 months, mid-complexity 4 to 8 months, and larger enterprise or regulated programs 8 to 18 months or more, often in stages. Integration with existing systems and government assurance stretches timelines most, so we give a range tied to your scope, with milestones rather than one distant deadline.

Yes. We typically deliver substantial projects in controlled phases, using short iterations, regular demonstrations and feedback cycles. This allows organisations to validate value early while retaining governance over scope, risk and investment.

By a local Australian delivery lead who owns the relationship, reporting and commitments, working in your timezone. Around that sits a regular rhythm of demos, progress and risk reporting, and a clear escalation path. For larger programs, we align with your internal steering or assurance structure.

Scope change is normal, so the delivery lead logs each one, assesses the impact on time and cost, and discusses it with you before proceeding. Risk is tracked live with owners and mitigations, reviewed in the regular governance rhythm. Our rule is that issues are raised the same day because problems are less expensive the earlier they're dealt with.

We manage delivery through strict scope containment, continuous risk tracking, and local accountability. Every engagement is assigned an Australian-based Delivery Manager who acts as your primary governance point.

Our post launch support continues beyond deployment through application maintenance, model monitoring, performance optimisation, security updates, infrastructure management, and ongoing enhancements. For AI systems, post-launch support can also include monitoring model performance, data quality, usage patterns, and changes that may affect production outcomes.

The start date depends on the project's scope, required expertise, access to systems and data, and governance or procurement requirements. For qualified projects, we can begin with a focused discovery phase to confirm requirements, technical dependencies, delivery milestones, and the team needed before development starts.

Appinventiv helps enterprises, government agencies, and growing businesses design, build, modernise, and scale technology that supports long-term business goals. Rather than focusing solely on software development, we work across the full technology lifecycle, from strategy and planning through implementation and ongoing optimisation.

Our core service areas include:

• AI Consulting Services
• Data services
• Product development & engineering
• IT managed & outsourcing
• AI Implementation and change management
• Legacy system modernisation
• Ongoing optimisation

Yes. We build custom enterprise software and integrate it with Microsoft, Azure, Azure OpenAI, SAP, Oracle, Salesforce, and REST APIs, alongside other enterprise applications and cloud environments. Integration is where enterprise projects get hard, so we connect through APIs, middleware and event-based patterns, with attention to data mapping, security and reliability. The state of your existing systems is the biggest variable, so we assess it early.

Yes, and a full rebuild is often an inappropriate approach. We preserve what works and replace only what holds you back: moving from monolith to modular components, re-engineering specific parts, adding modern interfaces or APIs over a stable core, or introducing data and AI. Staged modernisation usually carries less risk than a big-bang rebuild, so we recommend the least disruptive path that solves the problem.

We design, build and migrate cloud environments across AWS, Azure and Google Cloud, with Australian regions for residency-sensitive work, covering architecture, security and governance, reliability and scaling, and DevOps. Migration is rarely just lift-and-shift; the question is what to re-platform, what to re-architect and what to leave alone, balanced against cost and risk.

Yes. We build native and cross-platform apps for iOS and Android, including the backend, integrations and security behind them. The platform choice depends on your performance needs, features and budget, and we build for Australian conditions including reliable offline operation.

Both. Many of our Australian engagements involve joining an existing program to strengthen a specific area, whether architecture, cloud, AI, quality or dedicated capacity alongside your in-house team. We work within your existing tools, processes and governance.

Our software delivery process typically covers consulting, discovery, UX/UI design, solution architecture, development, QA, deployment and post-launch optimisation. The exact stages and governance are adapted to the project's complexity, risk and delivery model.

Quality assurance runs throughout the delivery process, not just at the end. Depending on the system, QA can include functional, regression, integration, API, performance, security, accessibility and user acceptance testing. The testing mix is determined by the system's complexity and risk.

We ensure code quality and long-term maintainability through peer review on every change, automated testing and static analysis in the pipeline, documented architecture, and consistent coding standards. The aim is to build secure and scalable software that your own team can maintain and extend, so we keep the codebase clean, documented and handed over in full. On modernisation work, we also reduce technical debt as we go rather than adding to it.

Yes. We build to the Web Content Accessibility Guidelines, and for government and public-facing work, we deliver to WCAG 2.1 Level AA, the level the Digital Service Standard expects (and WCAG 2.2 AA where a project requires it).

Accessibility is designed in from the start, covering keyboard navigation, screen-reader support, colour contrast and clear semantic structure, and we test with both automated tooling and manual checks against assistive technology. For government systems, we can provide an accessibility conformance report.

We start from business problems, not the technology. We look at where work is repetitive, slow, error-prone or bottlenecked, then score each aspect on three things: the value if it works, the quality of the data available, and the feasibility and risk of building it. The ones that score well on all three go first, and we usually prove a contained use case before committing to a broader program.

The success of an AI solution depends entirely on whether your team actually trusts and adopts it. We counter AI resistance and "tech anxiety" by involving end-users early in the scoping phase so the tool feels built for them, not to replace them.

Our engineering and design delivery supports your internal change management efforts through three pillars:

• Explainable UX & Guardrails: We design intuitive interfaces that clearly show why an AI model made a specific recommendation, which organically builds user trust and reduces skepticism.
• Handover Documentation: We provide your team with detailed system documentation, functional guardrail specifications, and operational guides to make internal upskilling straightforward.
• Iterative Feature Deployment: We roll out capabilities in controlled, manageable phases so your existing workflows can adapt naturally without causing operational friction.

Appinventiv delivers custom AI solutions across generative AI, predictive analytics, intelligent automation, conversational AI, computer vision, recommendation engines, and AI-powered enterprise applications. We can help organisations move from an AI use case or proof of concept to a production-ready solution, including model development, data pipelines, API integration, security, deployment, and ongoing optimisation.

Yes. We can integrate AI capabilities into existing enterprise environments without requiring organisations to replace their core systems. Our teams can connect AI models and applications with ERP, CRM, data platforms, cloud infrastructure, APIs, and business workflows while accounting for security, access controls, data governance, and performance requirements.

We deploy responsible AI under control, with governance built in from the start, covering data access, privacy, human oversight, output validation, monitoring and accountability. We also involve users early and roll out AI capabilities in controlled stages so teams can understand, test and adopt new workflows.

Yes. AI can be deployed within Australian or restricted environments with controls covering data minimisation, access permissions, encryption, audit logging and residency and other regulatory requirements. This includes the Privacy Act and APPs, local data residency, Essential Eight security baselines, and APRA standards for regulated financial clients.

We integrate AI through APIs and contained services, so it connects to what you already run rather than replacing it. The usual pattern is to start with one well-bounded use case, prove it in a controlled environment, measure it, then connect it into live systems and the workflows around it. Most of our enterprise AI work connects to existing CRM, ERP or analytics platforms.

We define the expected outcome before the build begins, then measure performance directly against it. Depending on the specific AI use case, this could include tracking hours saved, error rates reduced, faster resolution times, higher conversion rates, or lowered operating costs. We establish a clear operational baseline before launch so the business impact is completely provable. We avoid vague or generalised ROI claims.

Many organisations successfully launch AI pilots but struggle to scale them across the business. We help establish the foundations required for broader adoption, including governance frameworks, data readiness, security controls, operating models, integration architecture, and measurable success criteria. By validating value in a controlled use case before expanding, organisations can reduce risk, maintain compliance, and build a repeatable framework for enterprise-wide AI adoption.

Yes. We build retrieval-augmented systems, copilots and AI agents as controlled workflows, not open-ended chatbots. An agent retrieves the right context, reasons within defined boundaries, and acts only through approved tools, with permission-aware access. We add tool allowlists, execution checks and validation before anything writes back to a live system, so it can do real work without going off the rails.

Yes. We help enterprise and mid-market organisations separate emerging tech hype from practical commercial utility. Our engineers design focused proofs-of-concept (PoCs) to test emerging technology capabilities in secure sandboxes before committing to full-scale rollouts.

Yes, we support the major providers offering local hosting, such as:

We also support on-premises and hybrid environments when it suits your requirements. Because the underlying infrastructure is simply a means to a reliable, compliant result, so we tailor our approach to your specific needs.

Yes. We build cloud-native systems using modular services, containers and managed capabilities, designed to scale. It isn't right for everything, though; for some systems, a simpler architecture is more affordable to build and run, so we use cloud-native patterns where the scale and complexity justify them.

We usually recommend a mixed approach, not one method for everything:

• Re-host, moving largely as-is, for speed.
• Re-platform, targeted changes for cloud benefits without a redesign.
• Re-architect, where the long-term benefit justifies the cost.
• Retire or retain, since not everything needs to move.

We suggest the approach per system based on cost, risk and the value of moving, including residency requirements that point to specific Australian regions.

Yes. We work across cloud, on-premises and hybrid, which matters where organisations keep certain systems or data on-premises for sovereignty, latency or regulatory reasons. We design the architecture, integration and security to span the environments cleanly.

We treat both as design requirements, not add-ons.

• On security: network isolation, identity and access controls with MFA, encryption, logging and continuous monitoring, aligned to the Essential Eight where relevant.
• On resilience: high-availability architecture, backups and tested recovery, and the ability to keep critical operations running through disruption, which matters for APRA-regulated clients under CPS 230.

We size both to the system's criticality rather than applying one template.

Yes. We help build a roadmap that sequences cloud and technology change against business priorities rather than the other way round. We start with where you are now, what's working and what's constraining you, then map the steps to modernise, with cost, risk, dependencies and residency factored in. The output is a staged plan your teams can execute and assure, not a single big-bang move.

Yes. Specialist tech expertise can be added based on the technical or business requirements of the project. This may include AI/ML, generative AI, data engineering, cloud, cybersecurity, enterprise integration, DevOps, or industry-specific expertise.

We work across 35+ industries, with experience spanning government, financial services, mining and resources, energy, healthcare, transport and logistics, construction, agritech and enterprise retail. Delivery is adapted to each sector's regulatory, operational and technology requirements.

We start by understanding the sector's constraints, regulatory obligations, operational realities and existing systems, then shape architecture, security and delivery around them. The priorities differ: regulated finance leads with security and auditability, mining and logistics with offline and field use, government with residency and assurance and agritech with low-bandwidth connectivity, IoT edge-computing, and harsh environmental variables. The engineering discipline is consistent; the sector priorities are what make software fit the operating environment.

Yes. We routinely architect platforms for organisations operating under stringent regulatory oversight. Our engineering practices align with APRA's CPS 230 guidelines for operational resilience, the Privacy Act 1988 (including the Notifiable Data Breaches scheme), and the security standards detailed within the Australian Government Information Security Manual (ISM) and ASD Essential Eight.

1. Absolutely. We understand the physical and technical challenges of these industrial environments. Our experience includes developing ruggedised asset management interfaces, real-time fleet tracking portals, IoT integration for predictive maintenance, and offline-capable safety reporting applications designed to keep onsite, mobile workforces safely connected to central databases.

We include an initial period of post-launch support as standard, then an ongoing arrangement matched to your roadmap and SLAs, covering monitoring, fixes, security and dependency patching, platform updates and planned improvements. It's sized to your situation rather than sold as a flat package.

You retain ownership of the source code and project IP. At handover, we provide the source, documentation, deployment details and structured knowledge transfer so your team can independently operate, maintain and extend the solution.

Yes. We sign SLAs setting out response times, support levels and, where relevant, uptime commitments. Critical issues like an outage or data fault get the fastest response, typically within hours, with less urgent requests on defined turnaround times. The specifics are agreed per engagement and set explicitly so expectations are shared before an incident.

Yes. Support is available in Australian business hours, a practical benefit of local delivery, with round-the-clock coverage available for clients who need it. For many, business-hours support with a clear escalation path is the right balance; for systems where downtime is serious, we arrange extended or continuous cover.

Supporting remote and offline systems differs from an always-connected app, so we design programs for it. Monitoring accounts for intermittently connected devices, and we build in logging and sync behaviour that lets us see what happened on a device even when it was offline, so a field issue can be diagnosed once it reconnects.

Getting started with us is easy. You just need to fill out the contact form, submit an enquiry, or schedule an initial consultation to discuss your requirements. Our Australian team will soon contact you to set up a short discovery call in your timezone. A rough outline of your goals, scope and timeline helps; you don't need a detailed brief, a clear idea of the problem is enough.

You don't need a formal specification. A clear description of the problem, must-have features, existing systems, security or residency requirements, and an indicative timeline or budget is enough to begin scoping.

Yes. We'll sign an NDA before you share anything detailed, and every engagement is covered by confidentiality regardless. We can use your agreement or provide ours. Sign first, then share the details comfortably.

Your first point of contact is usually a consultant or product strategist who understands the technology and your sector, and who shapes the idea into a workable plan; once in delivery, a local delivery lead becomes your day-to-day contact. We aim to respond within a few working days with an initial view, possible approaches and a timeline range, and faster if it's time-sensitive.