Operations AI agent development and back-office AI agent development for Australian businesses. Agents that triage incoming work, route tasks, extract data from documents, manage approvals, and flag exceptions. Connected to your existing systems.
Perth-based. Australia-wide. Custom-built to your operational rules. Fixed-price scoping.
Three stages. No surprises. Every operational AI agent services project is delivered personally by the founder, from scoping call to production cutover.
Week 0
15-minute scoping call. We map your current process, the documents/data the AI will work with, and the systems the AI must act in. Fixed-price quote inside 48 hours.
Weeks 1–N
Operations AI agent built and parallel-run against your live workflow for two weeks. Every routing, action and integration validated before production. Human-in-the-loop where confidence is lower.
Cutover
Production cutover on a planned window. Team training, monitoring active, 30 days post-launch support. Documentation, rules and source code handed over in full.
Five agent patterns we ship most often across business operations AI agents work. Most projects combine two or three. Pick a tab to see how yours would take shape.
An AI agent that receives incoming work (job requests, service enquiries, internal tickets, forms, emails) reads them, extracts the key information, classifies them, and routes them to the right person or queue. Automatically.
Instead of someone manually reading every email and deciding where it goes, the agent does it in seconds. It picks up the request type, urgency, required skills, and relevant details, then routes it according to your rules.
An agent that reads incoming documents (emails, PDFs, forms, scanned paperwork) and extracts structured data. Names, dates, amounts, reference numbers, addresses, line items. The stuff your team currently re-types into systems manually.
The extracted data goes straight into your business systems: CRM, accounting, job management, or custom database. No manual data entry. No copy-paste. No transcription errors.
An agent that manages approval workflows. Purchase requests, leave applications, change requests, expense claims. The agent reads the request, applies your approval rules, and routes it to the right approver.
If the amount is under $5,000, it goes to the team lead. Over $5,000, it goes to the department head. Over $20,000, it needs two approvals. The agent knows your rules and follows them without fail.
An agent that monitors your operational data and flags exceptions: things that do not fit the normal pattern. Late deliveries. Incomplete records. Mismatched data between systems. Thresholds breached. SLA deadlines approaching.
Instead of your team discovering problems when a customer complains or an audit uncovers gaps, the agent catches them early. It flags the exception, categorises it, and sends it to the right person with context.
An agent that coordinates multi-step operational tasks across teams and systems. A new project starts and the agent creates tasks in your project management tool, assigns them based on availability and skills, sends notifications, and tracks completion.
The agent follows your standard operating procedure. When Step 2 depends on Step 1, the agent checks that Step 1 is done before triggering Step 2. When steps run in parallel, it tracks both and consolidates status.
No hourly billing, no vague estimates. Here is how operational AI agent services and AI ops automation services are scoped, from a free 15-minute call to a fixed-price proposal.
Tell us what problem you are trying to solve. We will give you an honest answer on whether AI is the right fit and what it would involve.
After discovery, you get a fixed price for the project. No hourly billing that spirals. You know exactly what it costs before we build.
PoC first, then production build in phases. You see real value early, give feedback, and pay in milestones.
Why HELLO PEOPLE
ChatGPT Enterprise, no-code AI tools and an in-house AI team all solve pieces of the problem. Here is how HELLO PEOPLE compares on the things that actually matter to an AU SMB.
| Concern | HELLO PEOPLE | ChatGPT / Off-shelf | No-code AI (Zapier) | In-house AI hire |
|---|---|---|---|---|
| Fit to your ops workflow | Agent modelled on your real ops | Generic chat, no ops context | Fine for a single-step trigger | Depends on who you hire |
| Ops agent live in 6-10 weeks | Live agent with alerts + fallbacks | You copy/paste alerts | You wire every ops trigger | Months to hire, then build |
| AU compliance + audit fit | Every action logged and reviewable | Opaque, no audit surface | Basic run logs only | You brief the hire on audit |
| Ongoing cost | One-off + optional support plan | Per seat/token, per month | Per-run + prompt engineering | Salary + super + overhead |
| When ops rules change | We update the rules and the guardrails | You wait for vendor updates | You rebuild the flow | Your team owns the rebuild |
| Direct access to the builder | Email Kasun, get Kasun | OpenAI support tier | Community forum | Internal AI team |
| Agent code + ops data ownership | You own the agent and the ops data | Vendor holds prompts + logs | You own the flow (self-hosted) | Your team owns it |
We helped an Australian firm replace hours of manual data entry with an intelligent processing pipeline. Documents captured via mobile now flow straight into backend systems, accurately and automatically.
Read the full case studyIncoming service requests used to sit in a shared inbox for hours before someone triaged them. The AI agent now reads them, classifies them, creates the job in simPRO, and assigns a technician in under a minute. We process 3x the volume with the same team.
Faster throughput, less manual admin, fewer missed items, live operations visibility. Here is what an AI ops automation project really delivers, not what a brochure promises.
The biggest operational cost is not the work itself. It is the waiting. Requests waiting to be read. Tasks waiting to be assigned. Approvals waiting for someone to notice the notification. Every manual handoff adds latency.
An AI operations agent removes the waiting. Incoming work is triaged in seconds, not hours. Tasks are assigned immediately based on availability and skills. Approvals are routed the moment they are submitted, with reminders if they stall.
One logistics client reduced average request-to-assignment time from 3.5 hours to 8 minutes. The work did not change. The waiting disappeared.
Data entry, copy-paste, manual triage, filing, routing. Your operations team spends a significant chunk of their day on work that does not need a human brain. It needs a human only because the systems are not connected.
An AI agent reads the incoming data, extracts what is needed, and puts it in the right place. No re-typing. No forwarding emails with "Can you please enter this into the system." No spreadsheet middlemen.
Your operations team gets to focus on decisions, relationships, and problem-solving. The work that actually benefits from human judgement.
When operations run on manual processes, things get missed. An email sits in the wrong inbox. A request gets filed but not actioned. An approval gets stuck because someone is on leave and nobody notices.
An AI operations agent tracks everything. Every request has a status. Every approval has a deadline. Every exception gets flagged. If something stalls, the agent sends a reminder. If a deadline approaches, it escalates.
The result is not just speed. It is reliability. Your customers and internal teams can trust that requests will be actioned, not lost in someone's inbox.
Most operations managers only see their pipeline when something goes wrong. A customer chases. A deadline passes. A team member flags they are overloaded. By then, it is too late to prevent the problem.
An AI agent with a dashboard gives you real-time visibility. How many requests came in today? Where are they in the pipeline? What is stuck? Which team is overloaded? Which processes have the longest lead times?
You make staffing, process, and priority decisions based on data, not on who shouts loudest.
Every project is different, but the six-step structure stays the same. Operations discovery, rules mapping, system review, build, testing with guardrails, then deploy and monitor once you are live.
A working AI agent connected to your systems that handles a specific operational process. It reads incoming work, applies your rules, and takes action in tools like simPRO, HubSpot or Xero. You get the agent, the integration code, dashboards, monitoring, and full source code. Every action is logged so you can audit what it did and why.
Fixed price after scoping. A single-process agent (intake triage or approval routing) sits at the lower end. A broader agent covering multiple processes and integrations is larger. Book a free 15-minute call, we run a paid discovery, and you get a fixed quote before build starts. Hosting, monitoring and model usage are scoped inside the same quote.
About 4 to 6 weeks for a single-process agent. 8 to 12 weeks for a multi-process agent with several system integrations. We start with the highest-impact process, ship it live, then expand. You see results in the first phase, not at the end of a 6-month build.
Yes. We integrate with simPRO, ServiceM8, Tradify, Monday, Asana, Jira, NetSuite, Dynamics 365 Business Central and MYOB Acumatica. If the system has an API or a database connection, the agent can read and write to it. Legacy systems without APIs get a small middleware layer.
Anthropic Claude and OpenAI GPT for the reasoning layer, depending on the task. We pick the model per use case based on accuracy, cost per action, and latency. Rules-based logic sits on top so the agent follows your business rules consistently, not just the model's best guess.
Normal. Our discovery includes mapping the actual workflow, not reading a manual that does not exist. We sit with the people doing the work, observe the process, and codify the rules. Building the agent is often the first time the process gets properly documented.
Yes. Data encrypted in transit and at rest. Role-based access controls. Full audit logging on every action. Data stays in your environment, hosted on Australian infrastructure by default. We do not use your operational data to train models.
That is how we recommend starting. Pick the process with the highest volume of repetitive manual work, deploy the agent there, measure the impact, then expand. Most clients add a new process every 2 to 3 months once the pattern is proven.
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Work sitting in shared inboxes, manual triage, data re-typed into three systems, approvals lost on someone's desk. Tell us what is slowing your operations down and we will come back with a clear next step and realistic cost.
Prefer a quick chat? Call 0425 531 127. We answer the phone in Perth.
