Frequently Asked Questions

AI works best when it understands your specific business. Start by identifying the knowledge your team relies on: pricing rules, compliance requirements, customer segments, approval workflows. Then look for tasks where that knowledge is applied repetitively. Good candidates include:

• Data entry and transfer between systems
• Report generation and formatting
• Customer inquiry sorting and initial responses
• Document processing and extraction
• Scheduling and coordination tasks

The key is structuring your business logic so AI can access it reliably. We help businesses capture that knowledge and build it into systems that work.

Start by documenting what you actually do, not what you think you do. Shadow yourself for a week and note:

• Every repetitive task
• Every manual copy-paste between systems
• Every time you think "there must be a better way"
• Tasks that frequently get forgotten or delayed

Then prioritise by impact: what takes the most time, causes the most errors, or blocks other work? Start small with one process, prove it works, then expand.

Cheat code: Use tools like Scribe to auto-document as you work. Or if you use Teams, Google Meet, or Zoom, join a meeting by yourself, hit record, and talk through the process out loud. Drop the transcript into Gemini (or your AI tool of choice) and ask it to create a step-by-step guide.

Not just yet, but quality is improving every day. AI is great at handling the boring, repetitive parts of jobs, not the parts that require human judgement, creativity, or relationship-building.

The businesses getting the most value from AI are using it to free up their people to do more valuable work. Your admin person who spends hours on data entry could instead be improving processes or helping customers directly.

Think of it as giving your team better tools, not replacing them.

We start with a free one-hour consultation. Not a strategy deck with hundreds of vague ideas, just a list of specific scenarios that will make an immediate impact on your business.

Setup costs depend entirely on the solutions and can start from £200–300. After that, ongoing costs are covered by a fair and transparent value-share model. No more flat SaaS fees for tools you don't use.

This model works for both of us. We're incentivised to build solutions that really work for you, while you only pay when you're realising that value.

Modern AI tools are increasingly user-friendly. You can use ChatGPT or similar tools right now without any technical background.

However, getting AI to work reliably for your specific business requires structuring your domain knowledge so AI can access it, connecting to your existing systems, and building the governance layer that keeps outputs trustworthy.

That's where we come in. We build the intelligence layer so you can focus on running your business.

Traditional automation follows fixed rules: if X happens, do Y. It's predictable, reliable, and works well for structured tasks.

AI can handle situations where the rules aren't clear-cut. It can interpret, understand context, and make judgements.

For example:

• Automation: File an invoice into a folder based on the sender
• AI: Read an email, understand what the customer is asking, and draft an appropriate response

Often the best solutions combine both: AI handles the interpretation, automation handles the execution. But both work best when they understand your specific business. That's the layer we build.

Simple automations can be live within days. More complex systems that touch multiple parts of your business typically take weeks to months.

The biggest factor isn't usually the technical work. It's capturing your business logic and domain knowledge well enough to build it into the system properly. Rushing this phase leads to automation that technically works but constantly needs human intervention for real-world cases.

We spend time upfront understanding how your business actually operates before writing any code. That knowledge capture is what makes the difference between automation that your team trusts and automation that your team works around.

This depends entirely on which tools you use and how they're configured. Key questions to consider:

• Does the AI service train on your data?
• Where is your data processed and stored?
• What are the data retention policies?
• Does it meet your industry's compliance requirements?

We help businesses navigate these considerations and implement AI in ways that meet their security and compliance requirements. For sensitive data, there are options to run AI models locally or use enterprise-grade services with appropriate data protections.