The AI Automation Agency That Runs Its Own Stack in Production.

Why most AI automation projects fail

The Australian market is now full of agencies selling AI automation. Most have never operated a production AI system at scale on their own business. They sell a deck, hand off to a junior implementer, integrate a chatbot widget, and disappear. Six months later the agent is hallucinating on routine queries, the integration with your CRM has silently broken, nobody is monitoring, and the project quietly dies.

The pattern is so common it has a name in the industry: demo to derelict. A demo runs flawlessly because it was scripted; production fails because real customers ask the questions you did not anticipate. Without engineering depth, observability, and an operations layer, an AI automation project is just a more expensive way to disappoint your customers.

How Iverel is structured differently

1. Engineer-led, not consultant-led. The person who scopes your project writes the production code. No handoff, no "account manager" layer, no requirements lost in translation.
2. We run what we sell. Our sister company ORCA Cleaning is our flagship customer. Voice agent, chat agent, quote engine, scheduling, document processing, 50-workflow back office — all live on the exact stack we deploy for clients.
3. Fixed-scope, fixed-price, written acceptance criteria. Every engagement starts with a written scope including the SLA, the metrics that constitute success, and the price. No surprise change orders.
4. Small live phases, not big-bang launches. The first end-to-end slice ships within four weeks of kickoff. Subsequent capabilities are added one at a time, each measured before the next is started.
5. You own everything. Source code, prompts, n8n workflows, integrations, knowledge base. We use open commercial platforms (Claude, OpenAI, Vapi, Deepgram, n8n, Supabase) so you can switch operators if you ever need to.
6. Observability from day one. Every interaction logged. Per-intent success rate, escalation rate, latency, and cost-per-interaction visible in a live dashboard. Drift alerts in Telegram or Slack.

Capabilities we build and operate

Iverel vs typical Australian AI agency

Engagement models

1. Discovery sprint (2 weeks). Paid scoping engagement. Operator interviews, workflow audit, candidate shortlist, written scope with fixed price for the build phase. Outcome: a go/no-go decision with full transparency.
2. Single-system build (3–6 weeks). One well-defined automation — typically a voice agent, a chat agent, or one back-office workflow. Live in production with full observability.
3. Multi-system rollout (8–14 weeks). Phased delivery of a connected stack — e.g. voice + chat + CRM workflow + document processing — with the first phase live within 4 weeks.
4. Ongoing operations. Monthly retainer covering monitoring, prompt tuning, model upgrades, small feature additions, and monthly performance reporting.

Pricing

All prices ex GST. Discovery cost credits against the build phase if you proceed. We do not charge change orders against the original scope — additions go through a written variation with its own fixed price.

Who this is for

Iverel is the right fit for Australian mid-market service businesses with 50–500 staff, AUD $7M–$150M revenue, and a meaningful volume of repetitive customer interactions — inbound calls, enquiry emails, quote requests, scheduling, document processing. Industries we work with most often include commercial cleaning and facilities management, property and strata management, professional services, allied health groups, RTOs, and B2B logistics.

We are a poor fit for one-person operations where the volume does not justify the build, for regulated medical or financial-advice applications, and for organisations looking for a software vendor rather than an engineering partner. If you want a chatbot SKU off a shelf, we are not your agency. If you want a production AI system that is yours, measured, and delivers a real ROI, we probably are.