We find what costs your company time, build the AI agents and automations that remove it, and train your team to run them. It starts with a 30 to 45 minute conversation.
Most companies have already tried something. A chat subscription, a tool someone saw in a video, maybe a pilot that never got past being a pilot. AI became a meeting topic and the day to day stayed exactly the same.
Meanwhile the processes stay manual. Proposals that take days. Support repeating the same answer. A report assembled by hand every week. Meetings that never turn into action. Expensive people spending hours on work that does not need a person.
That cost never shows up as a line called bottleneck in your accounts, but it exists and it grows every month. That is why nothing here starts with technology. It starts by finding out what the bottleneck costs, and removing exactly that.
The problem is not a missing tool. It is that nobody mapped where the tool turned into money.
We build the system inside your operation, on top of the tools you already use. Not a pilot, not a subscription, not a slide deck.
Your people learn to run it and to extend it. The handoff is the product, not something that happens at the end if there is time.
The system keeps getting better after we leave, for as long as you want it to. Optional, monthly, never locked in.
These are the nine AI solutions we implement inside a company. Every module on the list already has a version built and running somewhere, and that is the only reason it is here. No company buys all nine: the diagnosis points to the two to four that remove the most expensive bottlenecks, and those are the ones that get built.
Your operation's knowledge in one place, structured for both people and AI: context, processes, decisions, history and documents, with permissions so each team sees what it should. The agents read from the same source your team does, which is what stops them from inventing answers.
Built on the AI OS core that runs my own operation every day
Sales, support or concierge on the channel your customers already use. The agent qualifies, answers, routes and books, and hands over to a person at the point you decide. Ports to Instagram, Slack, Telegram and web chat with the same core.
Built on the agent that answers my own business WhatsApp in production
Email, calendar and documents with triage, drafting and scheduling done by AI. It proposes, you approve, then it sends. The gate is the point: nothing leaves the company without a human saying yes until you decide otherwise.
Built on a Google Workspace assistant with OAuth and an approval gate
Calls and meetings become structured records, decisions, action items and scheduled follow-ups. The pipeline runs from recording to task without anyone writing notes, so commitments stop depending on memory.
Built on a transcript to note to scheduled follow-up pipeline in daily use
Background workers that route incoming information, summarise what changed, alert the right person, assemble recurring reports and keep data tidy. They run on a server on a schedule, report when something breaks, and need no one to remember them.
Built on unattended workers running on a cheap VPS, monitored and logged
Research, drafting and review across channels, with a human editor in control of what ships. Volume without losing the voice, because the brand rules live in the second brain rather than in someone's head.
Built on multi-agent content swarms and a library of roughly 65 skills
On-page, technical, Search Console and visibility inside AI answers, operated by supervised agents. Optimising for what ChatGPT, Perplexity and AI Overviews cite is now a separate job from ranking on Google, and this module treats it as one.
Built on nine SEO and AEO skills used on live client sites
Google and Meta campaign building, structuring and optimisation with AI assistance, and an approval step before any change touches a live account. Budget decisions stay human on purpose.
Built on the Google Ads API and campaign work at marketplace scale
A customer portal, a booking system, an internal operations console, or a product you intend to sell. Designed, built, deployed and handed over, with payments, authentication and notifications where the case needs them.
Built on a multi-tenant booking SaaS live with paying companies
AI implementation here runs in four phases: diagnosis, implementation, handoff, then optional monthly improvement. Same sequence every time, whatever the modules turn out to be. The first three stages take roughly three months end to end, and payment is tied to delivery milestones, so nothing is paid upfront for work that has not happened.
The diagnosis is also the entry point on its own. You can buy stage one, get the bottleneck map and the roadmap, and stop there with something useful in hand. Nobody has to commit to a build before seeing the numbers.
Duration3 to 4 weeks
We talk to your team, map the processes and find where time and money are leaking. Every bottleneck comes out quantified: hours lost, money attached, and what it costs to leave it alone.
DeliverableBottleneck map, AI roadmap prioritised by return, and the proposed architecture.
Duration6 to 8 weeks
We build what the diagnosis prioritised and nothing beyond it. The foundation goes in first, then the two to four modules that kill the biggest bottlenecks, plus the integrations they need to actually act.
DeliverableFirst automations in production during the phase, not only at the end.
Duration2 to 4 weeks
We train the team, document the system and stay for 30 days of tuning. The goal is the opposite of consultant dependency: the system running in-house with the people you already have.
DeliverableTrained team, operating documentation, and a stable system in the day to day.
DurationOngoing, optional
Handoff is not the end of the relationship unless you want it to be. The optional retainer keeps the system improving: tuning what is live, adding agents as new bottlenecks surface, and folding in new capability as the models change.
DeliverableMonthly optimisation and new modules on request, renewed monthly, never locked in.
The investment is presented as a proposal after the diagnosis conversation, anchored in what the diagnosis found. There is no on-the-spot quote, on purpose: pricing a build before understanding the operation is how a company ends up paying for the wrong thing.
The group's own operation runs on these modules: a second brain, roughly 65 skills and agents working on a server around the clock. Every client project starts from something already running rather than an empty file, and that is the only reason a three month timeline is realistic.
The agent that qualifies and answers my own business enquiries on WhatsApp runs in production every day. It is the module I sell most often, and it can be demoed live rather than described.
A booking and reservations platform used daily by real companies, with payments, calendar sync and notifications. Proof that the software module ends in a product, not a prototype.
I designed and built a multi-agent growth marketing system for a large Australian marketplace, covering paid media, SEO and prospecting. That is where the growth modules were pressure tested against real budgets.
A single conversation about a print shop's workflow became a working operations console. That is the diagnosis motion in miniature: listen to the process, then build the thing that removes the friction.
The nine AI solutions are delivered by Mindex Studio. The other two companies exist because companies ask for two other things: teach us to do this ourselves, and build the software for us.
Serves clients. Growth and performance marketing, SEO and answer engine optimisation, and AI implementation inside the operation.
Teaches people to build AI systems that run day to day. Direct mentorship, structured programmes and a community.
SaaS and microSaaS implementation and development. Our own software, from product to paying customer.
The people doing the work touch the product. No account management layer between you and whoever executes, and the person who runs your diagnosis is the person who builds the system.
A performance claim with no number attached gets flagged as directional, never sold as a result. That rule applies to what we report to you and to what we say about ourselves.
Anything done twice gets written down. Anything written down gets automated when it earns it. That is why each build starts from something already running rather than from an empty file.
MAFIVI GROUP is the group that everything runs through. Inside it are three companies: Next Level AI for education and mentorship, Mindex Studio for client work including AI implementation, and Time4 for software. One group, one standard of work, three different kinds of buyer.
If you want AI implemented inside your company, that is where most conversations start, and it begins with a diagnosis. If you want your team trained to run and extend these systems, that is part of every build and can also be arranged on its own. If you want software built, or you are looking at booking software, that is Time4. When in doubt, write to us and it gets routed.
With a paid diagnosis, never with a build. Three to four weeks of talking to your team and mapping processes, ending in a bottleneck map with the cost of each bottleneck quantified in hours and money. Only then does anyone decide what to build, and the proposal comes anchored in your own numbers rather than in a generic package.
There is no price list here, on purpose. The investment is presented as a proposal after the diagnosis, anchored in what the diagnosis found: the bottlenecks, the hours they cost, and the modules that remove them. Payment is then split across four delivery milestones, so nothing is paid upfront for work that has not happened.
Roughly three months from the first conversation to a team running the system in house. Diagnosis takes three to four weeks, implementation six to eight, and handoff two to four. The first automations reach production during the implementation phase rather than only at the end. After that, the monthly improvement retainer is optional and renewed monthly.
Consulting ends in a plan. Implementation ends in a system running inside your operation, with your team trained to run it. The diagnosis produces the plan and can be bought on its own, but the work it leads to is a build and a handoff, not a pilot, not a subscription and not a slide deck.
Yes, and the shape changes with the size. An owner with a small team or none runs eight sessions, one at a time. A company with areas and teams runs the training programme in three layers. A company that wants the system built runs the diagnosis, the build and the handoff. Same work, three shapes.
No, and you should be suspicious of anyone who says yes. The nine are the menu. The diagnosis picks the two to four modules that kill the biggest bottlenecks, and those are the ones that get built. Selling all nine to one company would be selling scope, not results.
No. The system is built on top of what exists: your CRM, your WhatsApp, your Google Workspace, your documents and your spreadsheets. The rule is integrate, not replace. A tool swap only enters the conversation if the diagnosis shows the tool itself is the bottleneck.
It stays with the company, in the company's own accounts. Anything sensitive passes a human approval gate before it leaves: no agent sends an email, changes a campaign or answers a customer outside the approval rules we define together. Unsupervised automation on risky actions is out of scope, in writing.
Matheus Vizotto runs the diagnosis and designs the architecture, and builds alongside his own agents, with specialist contractors when scope requires it. There is no salesperson handing the project to a junior: the person who understood your bottleneck is the person who delivers the system that removes it.
We work with companies wherever they are. The diagnosis runs on conversations with your team plus forms, and the build is remote by nature, so your time zone is a scheduling detail rather than a blocker. We work in English and Portuguese, and on-site can be arranged when it genuinely helps.
Thirty to forty five minutes. We find out whether there is a bottleneck worth removing, and I tell you honestly if I cannot help.
