The average digital agency now runs more than ten separate software tools. Most of them don’t talk to each other. SimpleOnboarding is the bet that it doesn’t have to be this way.
Mojo Dojo has partnered with AI consulting firm in Melbourne – Zen Labs – to build SimpleOnboarding — a single operating platform designed to replace the fragmented, expensive software stack that most digital agencies have quietly duct-taped together over the years and have come, somewhat reluctantly, to depend on.
The project has been in development for several months, with Mojo Dojo’s agency operations expertise and Zen Labs’s AI infrastructure capability combining to take on a problem that is now well-documented across the industry, even if few operators have had the resources to fix it properly.
THE STACK PROBLEM, BY THE NUMBERS
The numbers behind this particular build are not flattering for the status quo. According to the Basis 2025 Advertising Agency Report , the number of agencies juggling ten or more tools jumped 131 per cent in a single year — yet agency productivity didn’t follow. Inefficient processes are now the number one challenge agencies face, cited by 56 per cent of respondents. Rising costs and shrinking profits came in close behind at 43 per cent each.
Meanwhile, Zylo’s 2025 SaaS Management Index puts average company SaaS spending at $49 million annually, up 9.3 per cent year on year, with the average organisation running 275 applications. That’s before the SaaS vendors themselves started moving the goalposts on pricing. Google Workspace raised prices by 17 to 22 per cent in early 2025. Atlassian followed with cloud increases of up to 40 per cent. The tools that once looked like efficient monthly line items are now compounding into a meaningful cost problem.
For agencies specifically, the drag shows up not just on the credit card statement but in the operational texture of the working week. Building one client report means logging into five different platforms. A content approval that should take an hour gets stretched across an email thread, a shared Google Doc and a Slack channel that three people aren’t watching. New business intake lives in a Google Form that fires a Zapier automation that somebody set up during COVID and has since become load-bearing infrastructure nobody wants to touch. NPS scores are tracked in a module nobody opens until a client threatens to churn. Call data is in Twilio. Social approvals are somewhere in the thread. The keyword research, the AEO work, the GEO strategy , each with their own workflow, their own login, their own subscription quietly compounding on the company card.
The combined effect isn’t just expensive. It’s slow. And in an industry where the margin between a good year and a difficult one is increasingly thin, slow is expensive too.
WHAT SIMPLEONBOARDING ACTUALLY DOES
SimpleOnboarding is being built to collapse all of it. Project and task management – currently fragmented across tools like Basecamp, Monday.com and Trello depending on which team lead set up their workspace. Client reporting, previously handled through platforms like AgencyAnalytics with their own login, their own data pipeline and their own export ritual, is absorbed into the same layer. Call infrastructure via Twilio, form-based intake, NPS and sentiment tracking all of it pulled into one operating surface rather than stitched together at the seams with third-party sync tools.
Content planning, ideation and approval flows get a dedicated home. So does social media scheduling and sign-off, a workflow that currently lives somewhere between a spreadsheet, a direct message and a vague collective memory of what was approved last Tuesday.
The automation logic, critically, is baked in rather than bolted on. The Zapier layer gets replaced by native workflow logic that doesn’t require a third-party account, a webhook, and someone who remembers the login details.
THE AI LAYER
Zen Labs brings the AI infrastructure, and this is where SimpleOnboarding moves beyond consolidation into something more structurally interesting.
The shift happening across search and discovery right now is not subtle. According to a comprehensive analysis by Conductor covering more than 3.3 billion sessions and 100 million AI citations, AI is not replacing search so much as replacing your website as the first place customers engage with your brand. The GEO Industry Report 2025 found that early adopters of GEO-ready content are being discovered up to ten times faster by generative engines compared to relying on organic SEO alone.
For agencies, this means the deliverables are changing. Answer Engine Optimisation (AEO) and Generative Engine Optimisation (GEO), the practices of structuring content so that AI platforms like ChatGPT, Perplexity, Google AI Overviews and Gemini can extract, cite and surface it in generated responses — are now core service offerings at firms that were pure SEO shops twelve months ago. As Power Digital’s Associate Director of SEO Strategy has noted, where AEO is about formatting answers, GEO is about earning them across an entire ecosystem of third-party mentions, reviews, forums and publishers. It is not just a content play – it is an entity strategy.
Most agencies are now expected to deliver on this. Very few have the operational infrastructure to do it consistently at scale. Research, tracking, reporting and workflow for AEO and GEO still largely happens across a patchwork of spreadsheets, monitoring platforms and manual processes. SimpleOnboarding is being built to integrate keyword and AI search research pipelines natively — surfacing insights rather than raw data, and connecting research outputs directly to content and approval workflows rather than requiring a human to manually bridge the gap.
Where most agency platforms still treat AI as a feature, SimpleOnboarding is being built with intelligence running through the operational layer itself. Research pipelines surface insights rather than raw data. Content workflows move from brief to approval with fewer human handoffs. Inbox monitoring flags what actually needs attention rather than everything. The goal is not to automate the agency out of the picture but to remove the coordination overhead that currently fills most of a senior account manager’s week and produces no client value whatsoever.
WHY BUILD IT IN-HOUSE FIRST
Mojo Dojo’s own operations serve as the platform’s first production environment. This is a deliberate choice and a meaningful one.
Most SaaS products built for agencies are built by people who have studied agencies from the outside. They correctly identify the problem — too many tools, too much friction, too much manual coordination — and then design a solution that addresses it in theory, tested against user interviews rather than daily operational reality. The gap between a convincing demo and a platform that actually works under the pressure of a full client roster, a mid-campaign pivot and a team member who is on leave is wider than most product roadmaps acknowledge.
Building inside the operation keeps the feedback loop short and the tolerance for half-finished features low. What gets prioritised is what actually creates friction on a Tuesday afternoon, not what looks elegant in a product review. What gets deprioritised is everything that felt important in the design phase but turns out to be noise when real work is being done. The result, in theory, is a platform shaped by operational necessity rather than feature aspiration — a distinction that tends to matter enormously once you start charging for it.
It also means that by the time SimpleOnboarding is taken to market, Mojo Dojo has something more persuasive than a demo. It has a working agency, running on the platform, doing real client work. That is a materially different commercial conversation.
The immediate focus is proving the platform works inside Mojo Dojo’s own operation — building out the core modules, stress-testing the integrations and establishing that the consolidation thesis holds when it comes into contact with the actual complexity of agency delivery.
SimpleOnboarding is a bet that the agencies most likely to thrive in the AI era are the ones who fix their operations first. The tools exist. The problem is that nobody has put them in the right order yet.