We build and manage a custom AI operator that works in the background for your business. It wakes on a schedule and on key events, checks the systems that matter, drafts and sorts the work, surfaces what needs attention, and routes every real-world action through owner approval. A chatbot answers when you ask. Managed Intelligence keeps working while you sleep and shows you what it did.
We design, build, and run an always-on AI operator tailored to your business. It has a heartbeat: scheduled checks, event triggers, clear work queues, approval gates, and reporting back to the owner. For Recycling King, we built an always-on agent named Reggie that handles emails, tenders, and leads. It drafts, sorts, surfaces what matters, queues important calls for quick approval, and keeps getting sharper as the business uses it. This is the premium, run-it-for-you option for owners who want the benefit of AI operations without needing to manage the technical layer.
Owners who want AI operating in the background but do not want to manage the technical setup themselves.
Businesses with valuable recurring work sitting in inboxes, tenders, forms, leads, documents or reporting queues.
Teams where speed, consistency and visibility matter, but owner judgement still needs to control important actions.
It is not suited to businesses looking for a cheap chatbot, or a fully autonomous system that acts without oversight.
A paid discovery process that defines the operator’s jobs, data sources, triggers, risk areas and approval model
Custom operator design covering scheduled checks, event-based actions, work queues and owner reporting
Connections to the business systems the operator needs to monitor, sort, draft and report on
Workflow build for priority use cases such as emails, tenders, leads, reporting, CRM checks or operational triage
Approval queues for real-world actions so the operator prepares the work and the owner controls the decision
Activity reporting that shows what the operator checked, drafted, flagged, escalated and handed off
Ongoing monitoring and improvement so the system is tuned against real business use rather than left static after launch
Sort new enquiries, prepare reply drafts, flag urgent items and keep the owner focused on the opportunities that matter.
Watch incoming tender or quote opportunities, summarise requirements, prepare next actions and surface deadlines early.
Check the key systems before the day starts and report what changed, what is blocked and what needs approval.
Create a named operator like Reggie at Recycling King, with defined jobs, work queues, approval points and continuous improvement.
We define the operator, its data, its jobs, and its approval boundaries.
Discovery maps the business systems, recurring work, risk areas, approval rules, and high-value tasks. The discovery fee is credited to the build if you proceed, so the first step produces a useful design whether or not you continue.
We design the heartbeat, triggers, workflows, and owner approval model.
We document what the operator checks, when it wakes, what events trigger action, what it can draft, what it can recommend, and what must wait for approval. The design includes reporting, error handling, audit trails, and escalation rules.
We build the agent, connect the systems, and test it against real work.
The build connects email, CRM, documents, forms, analytics, advertising, customer data, and industry-specific systems where needed. We test on real examples, tune the prompts and workflows, and make sure the operator produces useful work before it is trusted with live queues.
The operator starts working with every real-world action routed through you.
Launch starts with controlled operation. The agent can draft, summarise, sort, prepare, and recommend, but owner approval is required before calls, sends, submissions, publishing, spending, or material business changes happen.
We run, monitor, and improve the operator month by month.
We review activity, missed opportunities, approval patterns, data quality, and new use cases. The operator gets sharper over time because it is managed against real business outcomes, not left as a static automation after launch.
We define the operator, its data, its jobs, and its approval boundaries.
Discovery maps the business systems, recurring work, risk areas, approval rules, and high-value tasks. The discovery fee is credited to the build if you proceed, so the first step produces a useful design whether or not you continue.
We design the heartbeat, triggers, workflows, and owner approval model.
We document what the operator checks, when it wakes, what events trigger action, what it can draft, what it can recommend, and what must wait for approval. The design includes reporting, error handling, audit trails, and escalation rules.
We build the agent, connect the systems, and test it against real work.
The build connects email, CRM, documents, forms, analytics, advertising, customer data, and industry-specific systems where needed. We test on real examples, tune the prompts and workflows, and make sure the operator produces useful work before it is trusted with live queues.
The operator starts working with every real-world action routed through you.
Launch starts with controlled operation. The agent can draft, summarise, sort, prepare, and recommend, but owner approval is required before calls, sends, submissions, publishing, spending, or material business changes happen.
We run, monitor, and improve the operator month by month.
We review activity, missed opportunities, approval patterns, data quality, and new use cases. The operator gets sharper over time because it is managed against real business outcomes, not left as a static automation after launch.
All pricing is ex GST. Every engagement starts with a conversation, not an invoice.
$1,500 to $3,500 paid discovery, credited to the build if you proceed.
From $10,000 for a custom always-on AI operator built around your business.
$500 to $1,500 per month for monitoring, improvement, and ongoing operation.
A chatbot waits for you to ask a question. Managed Intelligence wakes on schedules and events, checks the work, prepares drafts, sorts priorities, and reports what it did. It is built to operate in the background, not just answer prompts.
No. This is the run-it-for-you option. We build, operate, monitor, and improve the system. Your role is to approve important actions, review the work that matters, and help us tune the operator around business priorities.
For Recycling King, their always-on agent Reggie handles emails, tenders, and leads. It drafts and sorts work, surfaces what matters, queues important calls for quick approval, and keeps improving as it sees more of the business pattern.
The default model is owner approval for real-world actions. The operator can draft, classify, summarise, prepare, and recommend in the background, but calls, sends, submissions, publishing, spending, and material changes are routed through approval.
An always-on operator needs clear scope, data access, approval rules, and risk controls before build work starts. Paid discovery gives you a proper design and fixed recommendation. If you proceed, the discovery fee is credited to the build.
Timing depends on scope, access and the number of workflows, but the process starts with discovery so the build can be properly estimated before implementation begins. More complex operators are staged so useful functions can go live before every future idea is built.
Yes. Managed Intelligence is designed to be reviewed and tuned from real use. We look at approvals, missed cases, draft quality, new patterns and business priorities so the operator becomes more useful month by month.
Answer a few questions and we will tell you the right first step, straight up. It even checks the practical stuff, like whether you have admin access to your own accounts, so there are no surprises later.
