Customer service agents
Handle enquiries, route tickets and draft responses across email, chat and phone.
AI agents | Perth + remote
Custom AI agents, built to work
Custom AI agent development for Australian businesses that need to automate real workflows across HubSpot, Xero and internal systems rather than stop at a chat window. Gartner predicts agentic AI will resolve 80% of common customer service issues autonomously by 2029. We build with Claude, GPT and the Model Context Protocol, reviewed, tested and production ready.
- Best fit
- Workflows that need bounded judgement, not rules alone
- Main deliverable
- A monitored agent with approval and failure paths
- Client input
- System access, representative data and an accountable owner
- Commercial model
- Fixed scope build with usage costs kept separate
Delivery ownership
- Scope
- Deliver
- Review
- Handover
The accountable team stays involved from scope through handover. Specialist capability is added where the work needs it, with responsibilities agreed before work starts.
The case
Agents move beyond the chat window
AI agents are the next step past chatbots. Instead of answering one question at a time, an agent can look something up, decide what to do next and carry out a task across multiple systems on its own.
The problem is that most businesses trying to set up AI agents end up with something that works in a demo but falls apart in production.
The agent hallucinates data, calls the wrong API, sends the wrong email or gets stuck in a loop. That gap between impressive demo and reliable business tool is where we operate, based in Perth and working with businesses across Australia.
Product delivery
A client view of the work
Josh and the VibeZero team turned a mess of ideas into a working product faster than I thought possible. They actually listened to what we needed, didn't overcomplicate things, and delivered something our team could use straight away. Genuinely one of the best tech experiences I've had as a business owner.
Scope
Agents that connect to your business
Every agent starts with a specific business problem, not a technology choice. We specialise in MCP, Anthropic's open standard for connecting models to external data and tools.
Customer and sales work
Handle variable enquiries and lead information within agreed communication and approval limits.
Sales and lead qualification
Score leads, enrich contact data and draft personalised follow ups automatically.
Knowledge and documents
Find, interpret and prepare information from the sources the agent is allowed to use.
Research and reporting agents
Pull data from multiple sources, compile reports and surface insights on schedule.Document processing agents
Extract data from invoices, contracts and forms, then feed it into your systems.Internal knowledge agents
Answer staff questions using your internal documents, SOPs and knowledge base.
Operations and monitoring
Coordinate work across systems, with a named owner and a recorded failure path.
Operations agents
Schedule tasks, manage approvals and coordinate between teams and systems.Data pipeline agents
Clean, process and route data between systems automatically.Monitoring and alerting agents
Watch dashboards, logs or feeds and take action when thresholds are reached.
If this is the work in front of you, send us the context. We will tell you whether this service is the right starting point before anything is scoped.
Method
How agent development works
Most agents deploy within two to four weeks. Simple agents with one or two integrations can be built in days.
Discover
Map the workflow
What does the agent need to do? Which systems does it talk to? What data does it handle? Where does a human stay in the loop?Design
Pick the right stack
Claude or GPT, connected through tools like n8n; we pick the plumbing so you do not have to.Build
Build and integrate
We connect the agent to your real systems, test with real data and iterate until it handles edge cases reliably.Operate
Deploy and monitor
Every agent ships with documentation, monitoring and a handover so your team knows what it does and how to manage it.
Agent or automation
Use an agent only where rules are not enough
Predictable triggers and actions usually belong in an automation. An agent earns its place when the work needs interpretation. A person still keeps control of consequential decisions.
Rule based
Workflow automation
Use it for known triggers, known rules and predictable outputs. It is easier to test and cheaper to run.
Bounded judgement
AI agent
Use it where the input varies and the system must interpret context. Approval, spending and external communication limits are agreed before the build.
Who it's for
Who AI agents are for
Professional services
Drowning in admin
Agents handle intake, scheduling, document preparation and follow up so your team can focus on billable work.
Mining & resources
Complex reporting
Agents pull site data, compile reports and flag exceptions. No more spreadsheet wrangling.
Ecommerce
Volume enquiries
Agents handle routine customer service enquiries autonomously, around the clock, with escalation boundaries.
Construction
Compliance tracking
Agents track certifications, chase documents and maintain registers without manual chasing.
Pricing
The workflow, build and running costs are separated
The agent build receives a fixed scope and price before implementation starts. The number of systems, data sensitivity, decision boundary and failure path determine the quote.
Before the build
Workflow and control boundary
The systems, permitted actions, approvals, failure path and acceptance checks are agreed first.
Approved project
Fixed build quote
The implementation, integration, testing, monitoring and handover scope receive a written price and timeline.
Ongoing costs
Usage and licences listed separately
Model usage, platform licences and other third party services stay separate unless the proposal says otherwise.
Model usage, platform licences and third party services are estimated during scope and billed separately from the build unless the proposal says otherwise.
Practical details
Questions about AI Agents
Commercial terms, delivery, ownership and fit, answered before a proposal is written.
An AI agent is software that uses a large language model like Claude or GPT to make decisions and take actions. Unlike a chatbot that only answers questions, an agent can read emails, update your CRM, generate reports, route leads and trigger workflows autonomously.
Start with the workflow
Begin with one bounded job for the agent
Every engagement starts with understanding your workflow.Enquiries get a reply within one business day.