We build AI systems that solve practical business problems — the kind that slow teams down, create admin bottlenecks, lose revenue, or stop good leads from being handled properly. These case studies show what that looks like in practice.
Every business has processes that look manageable on paper but break down in real life.
A team leaves site and forgets to log a change.
A lead comes in, but no one qualifies it properly.
An onboarding process eats up hours of admin that should never have been manual.
Our work sits in that gap.
We design AI systems that fit into the way teams already operate — through WhatsApp, chat, CRM, shared records, and structured workflows — so important information gets captured, routed, and acted on without relying on memory, manual chasing, or duplicated admin.
Using AI and WhatsApp to capture project changes in real time, update shared records, and keep pricing, scheduling, and deadlines aligned.
Kabilo had a common operational problem that becomes expensive over time. When the team returned from site, they still needed to update the job specification with anything that had changed during the day — extra requested work, small scope changes, project adjustments, timeline implications, or details that affected pricing and scheduling.
In theory, those updates were meant to be added later. In reality, people were busy, tired, moving to the next task, or simply forgot. The problem was not bad intent. It was that the process depended too heavily on people remembering to do admin after the work was already done.
Kabilo needed a way for project updates to be captured immediately, in the easiest possible format, using the tools the team already used day to day. They did not need more complexity. They needed less friction.
The goal was to make updates happen while the information was still fresh, then push those updates into a shared system the wider team could rely on later.
We built an AI chatbot workflow through WhatsApp that allowed the team to record site updates in real time. Instead of relying on someone to remember everything later and manually update the job specification, team members could simply send the update through WhatsApp as part of the normal flow of work.
This solved more than just "note-taking." It improved the way project information moved through the business. Instead of site changes being captured late, partially, or not at all, they became part of a structured operational workflow.
That meant better visibility, cleaner handoff between field and office, and fewer gaps between what happened on site and what the business believed was happening.
Alongside the operational workflow, we also built AI lead qualification into Kabilo's CRM. Rather than every enquiry being handled manually from scratch, the system helped capture and qualify incoming leads, then push them into the CRM in a cleaner, more structured format.
Guiding clients through onboarding in a structured and consistent way, reducing manual admin, and giving the team more time to focus on higher-value work.
Finstride, a financial management company, had a process that was valuable but time-consuming: onboarding new clients. Like many service businesses, the onboarding stage required a lot of repetitive communication — explaining next steps, collecting key information, asking the same qualification questions, and guiding clients through the process clearly and consistently.
That work mattered, but it also consumed a large amount of team time. The more time spent manually guiding clients through the same early-stage process, the less time the team had available for deeper, more valuable work elsewhere in the business.
Finstride needed a way to make onboarding smoother, more consistent, and less dependent on manual back-and-forth. They wanted clients to feel guided, supported, and clear on what to do next — but without requiring the team to personally handle every step of the same onboarding journey over and over again.
We built an AI chatbot designed to guide clients through the onboarding process. The chatbot acted as a structured first layer, helping clients move through the key stages clearly, while reducing the amount of repetitive work required from the Finstride team.
Instead of relying on staff to manually repeat the same onboarding instructions and collect the same information every time, the chatbot standardised that experience.
For Finstride, the value was not just speed. It was consistency, clarity, and time recovery. A well-designed onboarding chatbot makes sure every client gets a smoother experience, while also removing unnecessary pressure from the internal team.
Fewer repeated explanations. Less manual coordination. More available time for the work that drives deeper value for the business. And a client experience that doesn't vary depending on who happens to pick up the task.
These two projects solved very different problems, but the underlying pattern was the same.
In one case, the issue was operational updates being missed after site work. In the other, it was too much team time being consumed by repetitive onboarding.
In both cases, the opportunity was to remove friction from a workflow that mattered.
That is where custom AI works best:
We do not start with "where can we add AI?" We start with "where is the workflow breaking down?" Then we design around that.
That might mean capturing updates through WhatsApp, qualifying leads into a CRM, guiding customers through a process, or syncing information across internal tools so the next step always happens.
The goal is simple: build something the team will actually use, and that creates measurable operational improvement from day one.
Bring us the process that people keep chasing, forgetting, duplicating, or patching together manually. We will map the bottleneck, identify what should be automated, and design a system that fits the way your business already works.