Find where the hours go. Build the system that gives them back.
For owners, COOs and leadership teams who know AI matters but don't want another tool nobody uses. We examine how work actually moves through your business, then design assistants, automations and governance that release capacity in the team you already have. The aim is more output from your people, without adding admin roles or another per-seat licence for every problem.
What sits inside AI & Business Systems
- AI strategy & roadmapsAn AI roadmap built on evidence: nine lenses, a do-nothing baseline, confidence-labelled estimates and a Now/Next/Later plan your board can act on.
- AI assistants & knowledge systemsRole-specific AI assistants that answer from your own documents, cite the source and respect permissions. Built on Microsoft 365, Google or a custom stack.
- Business process automationAutomate intake, quoting, follow-up, onboarding and reporting across the systems you already use. Measured in hours released, with people on exceptions.
- AI-augmented workforceHelp your existing team do more valuable work with AI: role-based training, approved tools, prompt libraries and adoption tracking. Capacity, not cuts.
- AI governance & implementationAI governance for Australian businesses: a use policy, approved tools, data rules and human oversight, informed by OAIC and National AI Centre guidance.
How this differs from the usual provider
We start with the business, not the model
Many IT providers start from the platform they resell, and many AI vendors from the product they sell. We start from your commercial model and workflows, and every recommendation resolves to one of nine moves, including Buy and Leave alone.
Strategy and build under one roof
Advisory firms often hand over a roadmap and leave; development shops often build what they're asked without testing the case. We diagnose, design, build, train and measure, so the people who scoped the opportunity stay accountable for whether it works.
We use what we recommend
We're building Altitude's own operations on the same kind of systems, including an AI inbox-triage system and a custom finance platform. Our advice comes from living with the trade-offs, not from a vendor demo.
Signs you need this
If two or more of these sound familiar, there's likely time and money to recover.
AI use is happening without you
Staff are pasting client details into free chat tools because nobody has given them an approved alternative. The demand is real, and so is the privacy exposure.
Senior people doing junior work
Your best estimators, managers or advisers spend hours each week formatting, re-keying and chasing. You are paying senior rates for that capacity.
Growth means hiring for admin
Each new contract, site or service line adds coordinators rather than revenue-producing roles. Margin gets thinner as the business gets bigger.
Pilots that went nowhere
You trialled Copilot, ChatGPT or a vendor's AI add-on, and usage faded within weeks. The tool worked; the work around it was never redesigned.
What changes for the business
Capacity without matching headcount
Assistants and automations take drafting, re-keying and chasing out of skilled roles. The same team can handle more customers, jobs or matters before the next hire is needed.
Faster response on revenue work
Quotes, proposals and enquiry replies are drafted from your own templates and pricing rules, then checked by a person. Shorter turnaround means fewer opportunities go cold while they wait in someone's inbox.
Knowledge that stays in the business
Procedures, precedents and product knowledge sit in a knowledge system staff can query in plain language, with a citation to the source document. New starters reach competence sooner and fewer questions interrupt your most experienced people.
Consistency you can audit
Every automated step follows the same rules and leaves a log, so quality stops depending on who happened to do the task. That reduces the rework, errors and complaints that quietly eat margin.
Software spend that matches the work
We check whether AI you already pay for in Microsoft 365, Google Workspace or your CRM can do the job before anything new is built. You avoid paying twice for overlapping tools and add-on seats nobody opens.
Risk managed from the first system
Data classification, approved tools, human review and an AI register are set up alongside the first build, not after an incident. Leadership can approve AI use knowing where personal and commercial information goes.
What we deliver
The Altitude Diagnostic
A paid, senior-led review across nine lenses that sets out where the highest-value opportunities are, what to do about them, in what order, and what to leave alone.
AI roadmap and business case
A Now/Next/Later plan with each opportunity modelled against a do-nothing baseline and every estimate labelled by confidence.
Role-specific AI assistants
Assistants for estimators, account managers, coordinators or advisers, grounded in your documents and limited to what each role is already allowed to see.
Workflow automations
Intake, quoting, follow-up, onboarding and reporting flows across your existing platforms, with exception handling and a person approving what matters.
Enablement and adoption program
Role-based training, prompt libraries, internal champions and usage reviews, so new tools become part of how the work is done.
AI governance framework
An AI use policy, approved-tools list, data classification, AI register and incident process, sized to your organisation and its risk.
Technology we work with
- Microsoft 365 and Copilot
- Google Workspace and Gemini
- OpenAI models
- Anthropic Claude models
- SharePoint and OneDrive
- Zapier and Make
- Xero
- HubSpot, Salesforce and HighLevel
- Cloudflare
- Postgres
How it runs
Timings are indicative and depend on your systems, data and approvals.
Diagnose
The Altitude Diagnostic examines your business across nine lenses and produces a prioritised opportunity portfolio, the economics and a roadmap.
5 to 7 weeks (indicative)
Design
For the first priority, we map the target workflow, data access, permissions and human checkpoints, and agree the measures before anything is built.
1 to 3 weeks (indicative)
Build and pilot
A working version runs with a small group on real work, with usage and accuracy tracked against the baseline.
3 to 8 weeks (indicative)
Roll out and train
We extend to the wider team with role-based training, documentation and a named internal owner.
2 to 6 weeks (indicative)
Measure and extend
A monthly review of capacity released, adoption and exceptions, then the next item on the roadmap.
Ongoing
Worked example
Accounting firm: a knowledge assistant staff can trust, and an end to the document chase
An illustrative 60-person accounting and advisory firm loses senior time to routine questions, has no rules for AI, and chases client documents by email. The system starts with an AI use policy, then gives staff an assistant grounded in the firm's own procedures, with citations and permissions, and moves document collection into a client portal.
- Job created in the practice management system
- Portal sends the client a document checklist
- Uploads filed against the job
- Staff prepare the work
- Knowledge assistant answers from approved sources, with citations
- Manager and partner review
- Client sees status in the portal
Guardrails, fit and measurement
Guardrails we apply
- Personal and sensitive information stays out of publicly available AI tools, as the OAIC recommends. We use business services whose published policies say your data isn't used to train their models by default.
- Assistants inherit your existing permissions, so staff only get answers drawn from documents they are already allowed to open.
- A named person reviews anything customer-facing, financial or high-stakes before it leaves the business.
- You own the prompts, workflows, configuration and data, documented so another provider could maintain them.
- Every system is recorded in an AI register with its owner, purpose, data sources and next review date.
Not the right fit if
- You want a chatbot on the website by Friday. We start with how work moves through your business, which takes longer than installing a widget.
- Your core data lives in spreadsheets nobody trusts. We will probably recommend fixing the data and process first, which may be a platform or process move rather than AI.
- The brief is to cut headcount. We measure capacity released for higher-value work and design for people using the tools, so we are the wrong partner for a redundancy program.
What we measure
- Hours released per role per week, against the pre-launch baseline
- Turnaround on the target workflow, such as median quote or proposal turnaround
- Weekly active use of each assistant by its intended users
- Exception and correction rate on automated outputs
- Volume handled per full-time equivalent, such as jobs, matters or enquiries
- Software spend per employee, before and after
Pricing
AI, systems and platform work is scoped individually, usually after an Altitude Diagnostic or a fixed-scope discovery, so we don't publish project prices.
Questions, answered.
Where should we start with AI?
Start with the work, not the tool. The Altitude Diagnostic looks at where time, money and information are being lost across nine lenses, then ranks opportunities by value, effort and risk. Your first move may be training, or switching on a feature you already pay for, rather than a new build.
How much does an AI project cost?
AI and systems work is scoped individually, usually after a Diagnostic or a fixed-scope discovery, because cost depends on data quality, integrations and how many people will use it. We don't publish project prices, because a number without a scope would mislead you. For Marketing Department clients, an AI team assistant is available from $1,500 setup plus $300 a month, ex GST.
Is our data safe, and will it be used to train AI models?
We build on business services such as Microsoft 365 Copilot, the OpenAI API and Anthropic's commercial products, whose published policies say business data isn't used to train their models by default. Access follows your existing permissions, and we classify your data before anything is connected. We also follow the OAIC's recommendation not to put personal information into publicly available AI tools.
Will this replace our staff?
That isn't how we design or measure it. We report capacity created, such as hours released for higher-value work. You decide how to use that capacity: growing without extra admin roles, faster service, or less overtime. Where roles will change, we plan it with your managers before launch.
Do you only work with one AI vendor?
No. We work across Microsoft 365, Google Workspace, OpenAI and Anthropic models and the major CRMs, and choose based on what you already own, your data and your risk settings. Sometimes the right answer is a product you buy off the shelf, and we will say so.
Where this matters most
Start with the Diagnostic
A senior-led look at where AI and better systems would pay back in your business, and what to leave alone.
Sources
Third-party facts on this page, checked 14 October 2026.
- Guidance on privacy and the use of commercially available AI products, Office of the Australian Information Commissioner (OAIC). www.oaic.gov.au/privacy/privacy-guidance-for-organisations-and-government-agencies/guidance-on-privacy-and-the-use-of-commercially-available-ai-products
- Data, Privacy, and Security for Microsoft Copilot, Microsoft Learn. learn.microsoft.com/en-us/microsoft-365/copilot/microsoft-365-copilot-privacy
- Business data privacy, security, and compliance, OpenAI. openai.com/business-data
- Is my data used for model training?, Anthropic Privacy Center. privacy.claude.com/en/articles/7996868-is-my-data-used-for-model-training