Territory organisations often run lean teams across long distances, so time lost to retyping, chasing reports and repeating handovers costs more here than most places. Solve8 helps Darwin organisations decide where AI is worth the money, then builds it: process automation, reporting, Microsoft 365 and Copilot, and the governance that government and funders expect.
We also provide IT consulting in Darwin for teams choosing software or moving to the cloud, and custom software development for internal apps and portals that have to work for staff spread across remote sites.
Every engagement is scoped in writing with a fixed fee per phase. Start with our AI strategy and advisory service or go straight to process automation.
We start from the problem in front of you. The organisations below come in every size and share a kind of work that automation handles well. If one sounds familiar, a scoping call will tell you quickly whether there is a project worth doing.
In a small Territory team one person often handles accounts, payroll queries and reporting. Extracting invoices and forms automatically, with that person checking exceptions, gives back hours each week.
The NT Government's AI Policy applies to agency staff, contractors and service providers. Suppliers need to show how their systems meet it, and we write that evidence while we build.
Services delivered across Darwin, the regions and remote communities generate case notes, reporting to funders and compliance records. Automation helps when a person stays in charge of every decision about a client.
Accountants, lawyers, consultants and tourism operators answer the same questions every week. An assistant grounded in your own documents drafts replies, and staff approve what goes out.
Construction, logistics and field teams run jobs in one system and finance in another, with a spreadsheet in between. We connect them so the numbers agree without retyping.
Contractors to the Defence estate and to gas and energy operators carry security conditions and evidence requirements that shape what an AI system may touch.
Most enquiries from Territory organisations fall into a handful of patterns. Each has a well understood fix, and sometimes the right fix involves no AI at all. Our comparison of automation and manual processes covers how to tell the difference.
We move the source data into a model that refreshes on a schedule, so reporting becomes a review of figures that are already there.
Automated compliance reportingWhen procedures live in one person's head, every handover costs weeks. An internal assistant built on your own policies and procedures keeps answers available to whoever is in the role.
An assistant built on your own knowledgeExtraction reads the document, checks it against your records and sends mismatches to a person. The rest flows into the system of record.
Multi-agent document processingTools for regional and remote teams need to queue work offline and sync later, or run a local model with no internet at all. We design for the connection you actually have.
Offline AI with local modelsLegacy finance, case management and job platforms can usually be reached through the database, scheduled exports or a supported connector. We pick the least fragile route and document it.
Integrating legacy systems with AIA governed internal assistant, with data held in an Australian region or on your own servers, gives people a sanctioned option and gives IT a log.
How the wrong AI tools leak business dataThe NT Government's Artificial Intelligence Policy sets requirements for any AI system, tool or component used by its agencies, whether procured, developed in-house or publicly available. It applies to staff and also to contractors and service providers, so a supplier's tools fall inside it.
The companion AI Assurance Framework gives agencies ethics principles, a self-assurance assessment and a quick risk assessment to authorise AI use. The policy also endorses Microsoft Copilot with enterprise data protection as a generative AI tool for public sector officers, which makes Copilot readiness a practical question for agencies now.
The Territory Government has also been building in-house AI and digital service design capability. For suppliers, that means agency buyers who understand the technology and ask sharper questions.
A data flow diagram, the hosting location, vendor training terms, a list of every automated step and the person who reviews it, and answers mapped to the self-assurance assessment.
See what this would take in your business
A free 30-minute review on Microsoft Teams. Bring the process you want fixed and leave with a clear first step.
A lot of Territory service delivery happens far from Darwin, in regional towns, homelands and remote communities. AI built for a city office often fails there. These are the questions we work through before anything is deployed outside a metro setting.
Many communities and stations rely on satellite or patchy mobile coverage. Tools must keep working offline, queue changes and sync without losing records.
Where people speak an Aboriginal language or Kriol at home, an English-only chatbot is a barrier. Test any client-facing tool with the community before it goes live, and keep a person reachable.
Data about Aboriginal people and communities carries obligations beyond the Privacy Act. The Maiam nayri Wingara principles set out community rights over how that data is collected, used and shared.
Automation should free up staff time for clients. It should never replace the person who makes a decision about someone's care, housing or payments.
For organisations working with Aboriginal communities, the right first step is often a conversation with the community and its organisations about what data is collected and who controls it. Our guide to AI governance and human override covers the technical controls, and aged care compliance and AI covers one of the sectors where care records and reporting meet.
With small teams and long distances, a failed pilot costs a Territory organisation more than most. Advisory work settles which projects are worth doing with a costed document that you own whether or not you build with us.
Our article on AI strategy compared with AI implementation sets out when to start with advice and when to go straight to a build, and the factors behind a successful pilot apply wherever you are.
Candidate processes across finance, service delivery, HR and operations, ranked by payback and difficulty.
Which systems connect, where the data lives, how it behaves on a poor connection, and what must change first.
Build and running costs set against current effort, written to survive a finance review.
Privacy obligations, data residency, human review points and the evidence the NT AI Assurance Framework asks for.
A pilot on one process first, so the approach proves itself before budget goes to a program of work.
We name the tools that fit, including tools we do not sell. You own the document and can execute it with anyone.
Copilot answers from whatever each user can already open in SharePoint, OneDrive, Teams and Outlook. Microsoft documents this directly: Copilot only surfaces organisational data the individual user has at least view permission to. With staff turnover, old project sites and shared mailboxes, permissions drift, and Copilot makes that drift visible.
The Digital Transformation Agency's evaluation of the Australian Government Copilot trial reported that participants saw Copilot surface sensitive information that had never been stored or permissioned properly.
So readiness work happens before the licences are bought: audit, fix or contain, then pilot.
Sites open to everyone, anonymous links, broken inheritance and ownerless sites, from SharePoint Advanced Management reports.
Where client, case, payroll, HR and board material lives, and whether Purview sensitivity labels cover it.
Restricted Content Discovery keeps risky sites out of Copilot answers while the clean-up finishes.
A group with clean access, measured tasks, and an agreed rule for buying more licences.
We build Power BI models that refresh from the systems you already run, with a written definition for each measure. For Seymour Whyte, a Tier 1 infrastructure contractor in the VINCI group, we replaced emailed spreadsheets with standardised templates, SharePoint and Power BI for carbon reporting, as described in the Seymour Whyte case study. Groups with several Xero organisations can start with ReportingMate.
Most organisations already own Power Automate through their Microsoft licences, and often a flow is the right tool. This is the test we apply.
Many good designs use both. For the wider tool choice, see our comparisons of AI and RPA and of AI agents and chatbots. Where the job needs something no platform offers, we take it on as custom AI development.
See what this would take in your business
A free 30-minute review on Microsoft Teams. Bring the process you want fixed and leave with a clear first step.
Darwin hosts Robertson Barracks and RAAF Base Darwin, with RAAF Base Tindal near Katherine, and two LNG export plants operate on Darwin Harbour. Suppliers to the Defence estate work under the Defence Industry Security Program, whose members appoint a Chief Security Officer and a Security Officer and hold clearances to suit their membership level. Those conditions decide what an AI system may touch, so for that work we default to models running inside your own environment.
Gas and energy facilities hold historian, maintenance and emissions data in separate systems. We read from them without writing back to control systems, for work such as Safeguard Mechanism reporting, alarm rationalisation and shutdown scoping from historian trends. Our processing and manufacturing page covers the plant side.
Our principal consultant spent 18 years on projects for resources and energy companies including BHP, Rio Tinto and Senex Energy, delivered while working with previous consulting employers. These companies are not Solve8 clients.
Territory organisations handle personal information under the Privacy Act 1988 or the NT's own information laws, and many hold sensitive client and community data. AI raises questions those rules did not anticipate: where a prompt is processed, whether a vendor trains on it, and who can explain an automated decision.
We default to Australian cloud regions. For sensitive workloads we deploy open models on your own servers or private cloud. See Australian compared with offshore AI development.
Private AI infrastructureFrom 10 December 2026, amendments to the Privacy Act require privacy policies to describe substantially automated decisions that significantly affect individuals.
Privacy Act rules for automated decisionsThe systems we build log inputs, outputs and the person who approved each exception, so an auditor can trace a figure back to its source.
Human approval in an HR assistantThe Cyber Security Act 2024 introduced ransomware payment reporting, and any AI system adds a new path into your data that needs the same controls as the rest.
Cyber Security Act 2024 and AIEngagements are scoped and fixed per phase, so stopping after discovery is a legitimate outcome and you are never locked into a build you have not approved.
A free 30 minute call, then a written scope with a fixed fee for the first phase. You decide before any work starts.
Workshops in the room with the people who do the work, and the rest over Microsoft Teams. Regional visits are planned in the scope.
Short build cycles against your real data, in your environment or an Australian cloud region. One process is piloted before any rollout.
Documentation, training and admin access stay with you. Your team runs it from there, or we look after it under a managed service.
After handover, some organisations keep us on through managed AI services, which suits teams without in-house developers, and teams that have them sometimes prefer team augmentation. Our AI consulting buyer's guide and how to choose an AI consultancy list the questions to ask any firm, including us. For a quick read on where you stand, try the AI readiness assessment.
We design for the connection and the team you actually have, we tell you when a project will not pay for itself, and the person who scopes the work also does it.
Each phase has a written scope and a fixed fee, so you approve the cost before work starts and can stop after any phase.
The consultant who scopes the job also builds it, with no account manager in between and no handoff to a junior team after the sale.
We build and operate our own software, including Carbonly for emissions data and SupportAgent for on-premise incident investigation. Both are the founder's own products.
Australian business, working nationally
Australian regions or your own servers
Governance written into every scope
Registered Australian business
Our principal consultant brings 18 years of enterprise delivery experience from projects for BHP, Rio Tinto and Senex Energy, delivered with previous consulting employers. These companies are not Solve8 clients. You work directly with senior people, not a sales team handing you off to juniors.
Practical guides on the questions that come up most in NT scoping calls
Common questions about AI consulting for Darwin and Northern Territory organisations
Have a question about AI for your Territory organisation that is not covered here?
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