The Approach

Understand before you implement.

There's a moment in every AI implementation where someone says, "But what if we just..." and everything that follows is wrong. Not because they're wrong about what's possible. But because they skipped the part where they actually understood the problem.

We don't skip that part.

Our approach is built on a simple principle: you cannot solve problems you don't understand, you cannot implement solutions you haven't properly designed, and you cannot deploy AI into a business without knowing exactly what breaks and why. Everything we do flows from that.

The discovery session: Six phases in three hours

The discovery session is the foundation. This is where we map your world—every system, every person, every pain point that AI might touch. We don't do this with surveys or off-the-shelf frameworks. We do it by sitting with you, asking sharp questions, and building a genuine picture of how your business actually works.

Here's how it breaks down:

Phase 1: Systems Audit

We start with the infrastructure. What systems do you use? Accounting software. Case management. CRM. Email. Document storage. Spreadsheets (you know there are spreadsheets). How do they talk to each other? Which ones don't? What's automated and what's still manual?

This isn't theoretical. We want to know the actual flow of information through your business. Where does data enter? Where does it live? Where does it come out? What gets copied manually from one system to another? Where do humans have to bridge the gap because the systems aren't talking?

The goal: a complete map of your technical landscape. Not to judge it. To understand it. Because everything that happens next sits on top of this foundation.

Phase 2: People Audit

Systems don't work in isolation. People work with systems. So we ask: who does what? Not job titles and descriptions. Actual work.

Who spends their day doing research? Who's reviewing documents? Who's writing emails and letters from templates? Who's doing data entry because the software doesn't integrate properly? Who has deep expertise but spends half their time on admin? Who's the actual champion of change—and who's going to resist it, and why?

We also ask about skills. Not "are you technical," but "who understands the infrastructure? Who's the person who's figured out how to make the systems work together even though they weren't designed to?" These are your leverage points. These are the people you're going to need when something changes.

And we listen for concerns. People aren't resistant to change because they're stuck in their ways. They're resistant because they can see real risks you haven't articulated yet. A lawyer is nervous about AI because they have a client confidentiality obligation. An accountant is nervous because an error has real consequences. Listen to that. There's wisdom in there.

Phase 3: Pain Point Analysis

Now we get specific. Where does time get wasted? Where do errors happen? Where are people doing work a computer could do? Where are decisions made based on incomplete information because completing that information by hand is too expensive?

These are different questions. A bottleneck isn't necessarily a pain point. Doing something by hand isn't painful if you only do it once a month. But doing something by hand 50 times a day when a machine could do it? That's a pain point.

We ask: if you could automate one thing this year, what would it be? And then we dig deeper. Why that thing? How much time would it save? What would the team do with that time? What could go wrong? What's the actual business impact?

We also ask about errors. Where do mistakes happen? What's the cost of a mistake—not just the time to fix it, but the impact on the client, the firm, the relationship? Some errors are expensive. Some aren't. We need to know which is which.

Phase 4: AI Opportunity Mapping

This is where we connect the dots. For each pain point, we ask: can AI actually help? And if it can, how?

Sometimes the answer is yes—clearly, definitely, with measurable ROI. A law firm reviews contracts manually. AI can automate that review. A financial planning firm does scenario analysis by hand. AI can do that in seconds. An accountancy firm extracts data from emails. AI can do that more accurately and faster.

Sometimes the answer is no. Not because AI isn't powerful. Because it's the wrong tool. Maybe the problem is a process that should just be fixed. Maybe it's a cultural issue. Maybe it's a people problem where more automation makes it worse, not better.

We're honest about both. Our job isn't to find AI solutions. Our job is to find real solutions. Sometimes that's AI. Sometimes it's not.

When AI can help, we map it out in detail. What exactly would we automate? What data would it need? Where does that data come from? What does success look like? How would you measure improvement? What's the timeline? What's the cost? What's the payoff?

Phase 5: Compliance Framework

This is where most consultants get uncomfortable. We don't. We sit with your IT team, your legal team, and your HR team and we build guardrails before we build anything.

IT asks: Where does data live? Who has access? Can we audit what the system did? Is there a backup? What happens if it fails? Can we turn it off tomorrow if we need to?

Legal asks: What about client confidentiality? Privilege? Data retention? Are we compliant with our obligations? What are the liability implications? Do we need to tell clients?

HR asks: How does this change people's work? What training do they need? Are there roles that change? Are there concerns we should address before this goes live?

We help you answer these questions during discovery, not after implementation. Because the time to think about compliance is before you've already built something that breaks it.

For sensitive data, we discuss the local LLM option. If your data is confidential, you can run the LLM on your own servers or a private cloud. It's slower than cloud AI. It costs more to set up. But it means your data never leaves your infrastructure. For professional services firms handling sensitive information, that's often the right trade-off.

Phase 6: The Roadmap

By the end of three hours, you have a prioritised action plan. We've identified the opportunities that matter most. We've understood the constraints. We've built in the compliance requirements. Now we build the roadmap.

What's the first thing to implement? What skills or infrastructure do you need? What training? What's the timeline? What's the cost? What's the expected payoff? How do you measure success?

We give you a clear sequence. You don't have to do everything at once. You do the thing that creates the most value first. You learn from that. Then you do the next thing.

And critically: you have an honest understanding of what this costs, how long it takes, what it requires, and what you can expect at the end.

After the discovery session

The discovery session is the map. What happens next depends on where you want to go.

Some firms use the roadmap and implement with their own team. We're happy to provide detailed documentation and training.

Some firms want us to implement. We can do that. We build the system, integrate it with your existing infrastructure, test it with your actual data, train your team, and hand it off.

Some firms want ongoing support. As you use the system, you'll learn things. You'll want to adjust it. You'll find new opportunities. We can be your AI engineering team—building, optimising, and scaling as your needs evolve.

The point is: you decide what happens next based on a genuine understanding of what you need and what it costs. Not based on a sales pitch or a template.

Working with your IT department

We've learned something important: IT departments aren't obstacles. They're partners. They understand your infrastructure better than anyone. They know what's secure. They know what's fragile. They care about uptime and compliance because they're the ones getting paged at 2 AM when things break.

Every implementation we do includes IT. Not as an afterthought. From the start. We ask: what do they need to know? What concerns do they have? What infrastructure do we need? What monitoring do we need? What's the backup plan?

The best implementations are the ones where IT is bought in from discovery to deployment. That's what we build toward.

The local LLM option

Not all AI needs to go to the cloud. If you're handling sensitive information—client details, legal advice, medical information, financial data—you can run the AI model on your own infrastructure.

This is slower. It costs more upfront. But it means your data never leaves your servers. Your compliance obligation is clearer. Your audit trail is cleaner. For many professional services firms, this is the right choice.

We help you understand when it makes sense and how to implement it. We're vendor-independent, so we'll recommend what's right for you, not what's easiest for us.

Training and change management

A beautiful system that nobody uses isn't a system. It's a feature. So we invest in training and change management.

After deployment, we work with your team to make sure they understand the system, feel confident using it, and actually do use it. We identify the champions—the people who are going to drive adoption. We address concerns. We gather feedback. We iterate.

Change is hard. Especially in professional services, where people are doing highly skilled work and don't appreciate having their job altered without understanding why. We take that seriously. We explain the why. We show the benefit. We listen to concerns. We adjust.

The goal isn't just to deploy AI. It's to deploy AI in a way that makes your team better at their jobs and makes the firm stronger.

Ongoing support and optimisation

AI isn't a one-time thing. It evolves. Your business evolves. The models improve. New capabilities emerge.

We can be your ongoing AI team. We monitor performance. We look for new opportunities. We integrate new capabilities. We scale what works. We shut down what doesn't. We're your partners in getting better over time, not a vendor you hear from at renewal.

Ready to understand your business?

The discovery session is not a sales call. It's a genuine attempt to understand your firm, your constraints, your opportunities, and what AI can actually do for you.

If you're curious about where this leads, let's talk.

Book a free 30-minute introductory call →

Or reach out directly:

Email: hello@corsza.com
Phone: +61 2 1234 5678
Location: Sydney, Australia

We'll spend three hours understanding your world. Then we'll tell you what we think, why we think it, and what happens next if you want it to.