Inside Our Discovery Process: How We Scope a Project

We Start With the Problem

The first conversation is about your business — not AI. We want to understand what's currently taking too much time, where your team is running into problems, and which processes are difficult to manage as the business grows.

Sometimes the problem is obvious — for example, your team may be spending hours every week processing leads manually. Other times, the real problem is further down the process. That's why we take the time to understand what's happening before suggesting a solution.

We Map How the Process Works Today

Once we understand the problem, we look at the current workflow. Who does what? Which tools are involved? Where does information come from, and where does it go? And where do things usually slow down or get missed?

For example, a typical sales process might involve a website form, email, a spreadsheet, a CRM, and several manual follow-ups. Mapping these steps helps us see the process as a whole rather than focusing on just one part of it.

We Identify Opportunities for Automation

Not every step should be automated. Some tasks require human judgment, while others are repetitive and predictable enough for software to handle.

We look for areas where automation can remove unnecessary manual work, reduce errors, improve response times, or make information easier to manage. Where AI can add value — such as understanding text, categorizing information, summarizing conversations, or making recommendations — we consider AI as part of the solution. But if a simple automation can solve the problem, we won't add AI just for the sake of using it.

We Look at Your Existing Tools

Before recommending new software, we look at what you're already using. You may already have a CRM, accounting platform, email system, spreadsheets, project-management software, or other tools that can be connected.

In many cases, the best solution isn't replacing everything — it's making your existing systems work together more effectively. This can also make an automation project faster, simpler, and less expensive.

We Define the Scope

Once we understand the process and the opportunities, we define what the project should actually include. This means getting specific about:

• What will be automated
• Which systems will be connected
• Where AI will be used
• What will remain manual
• What the expected outcome should be
• How success will be measured

A clear scope helps everyone understand what we're building before development begins. It also prevents a common problem with automation projects: starting with one small idea and gradually turning it into something much larger and more complicated than originally planned.

We Prioritize Based on Business Value

There may be several things we could automate. That doesn't mean we should do all of them immediately. We look at the potential impact of each opportunity and prioritize the ones that are likely to create the most value.

A process that takes your team five minutes once a month probably isn't the first thing to automate. A process that takes someone two hours every day is a very different story. The goal is to focus your investment where it can have a measurable impact.

We Give You a Clear Path Forward

At the end of the discovery process, you should have a much clearer picture of what can be improved and what it will take to do it. Depending on the project, this may include a proposed workflow, recommended tools, integration requirements, estimated scope, and a plan for implementation.

And sometimes, the conclusion is that automation isn't the right solution for a particular problem. We're comfortable saying that too.