What do you do that ChatGPT can't?

ChatGPT is a tool. We build systems. We connect AI to your data, your apps, and your workflows. You get a custom solution that works for your business, not just a chatbox.

How long does a project take?

Most projects take 2 to 6 weeks. Quick automations take 2–3 weeks. Complex AI systems take 4–6 weeks. We'll give you a clear timeline on our first call.

What if I don't know anything about AI?

That's fine. Most of our clients don't. You tell us the problem. We figure out the fix. We speak plain English, not tech jargon.

Do you offer ongoing support?

Yes! We offer monthly support plans. We fix bugs, add features, and keep things running smooth. We want to be your long-term partner, not a one-time vendor.

How much does it cost?

Projects start at $1,000 USD. Quick automations run $1k–$3k, custom RAG systems $3k–$10k, and complex AI builds $10k+. You get a clear quote before we start. No hidden fees.

What's the Free AI MVP program?

We select 3 qualified businesses each month to build a free, small-scale AI prototype in 2–3 weeks. It lets you test our engineering and see real value before committing to a full build.

Agentic AI vs Traditional Automation: What's the Real Difference?

The Automation Spectrum

When people say "automation," they usually mean one of two things:

Workflow automation — tools like Zapier, Make, and n8n that follow fixed if-this-then-that rules.
Agentic AI — autonomous systems that receive a goal and figure out the steps themselves.

Both are powerful. Neither is a replacement for the other. Understanding the difference will help you know which to deploy for which problem.

What Traditional Automation Does Well

Tools like Zapier, Make.com, and n8n are exceptional at:

Predictable triggers: When X happens, do Y. Every time, without exception.
Data movement: Syncing CRM records, moving files, updating spreadsheets.
Notification workflows: Alert the team when a deal closes.
Simple sequences: New lead → enrich → add to CRM → send welcome email.

The key word is predictable. These tools require you to define every possible path in advance. If a situation arises that you didn't script, the workflow breaks.

Where Agentic AI Is Different

Agentic AI systems — built with frameworks like LangChain, LangGraph, and CrewAI — work differently.

You give the agent a goal, not a script.

Example: "Research the top 10 competitors in the UK SaaS payroll market, identify their pricing, and produce a competitive analysis report by tomorrow morning."

A traditional automation can't do this. There are too many unknown steps, too many decisions to make along the way. An AI agent can:

Decide to use web search to find competitors.
Visit competitor pricing pages and extract data.
Use an LLM to analyse the data and identify patterns.
Format and deliver the report.

The agent makes decisions. Traditional automation executes decisions you already made.

The Practical Decision Framework

Use n8n / Zapier / Make when:

The workflow has clear, fixed steps
Inputs and outputs are predictable
Speed of execution and reliability are paramount
You want low ongoing cost

Use Agentic AI when:

The task requires judgment or research
Steps aren't known in advance
You want something that adapts to novel situations
You're replacing a knowledge worker's repeatable work

The Best Systems Use Both

The most powerful setups we've seen combine both layers:

n8n captures a new lead from a form → AI Agent researches the lead company, qualifies against ICP, drafts a personalised outreach email → n8n logs the result in HubSpot and triggers the email send.

Traditional automation handles the predictable plumbing. The agent handles the intelligent work in the middle.

Ready to combine both in your stack? Talk to us about AI automation design.