AI Automation.
Automate the work that repeats. Keep the humans on the work that doesn't.
Most automation projects fail because they tried to automate the wrong thing. We map your week, find the 3 to 5 tasks that actually repeat, and build the workflows that save real hours. No agents. No buzzwords. Just work that stops getting typed twice.
The work starts with mapping. We sit with you for half a day and you walk us through your week, hour by hour. We find the 3 to 5 tasks that you (or someone on your team) do every week, that follow a pattern, and that mostly do not need a human judgment call. Lead intake from the website that gets manually entered into the CRM. Invoices that get pulled from email and dropped into accounting. Customer-support tickets that get categorized by a person who has done it 4000 times. Each of those is a candidate.
The lie the SaaS world is selling is 'AI agents will run your business'. They will not. Not this year, probably not the next. What works right now, and works reliably, is deterministic workflows with AI in the middle for the parts that need judgment. A Zapier flow that watches your inbox, an OpenAI step that categorizes the email and pulls the relevant data, a write to the CRM, a notification to a human if anything looks off. Boring. Reliable. Runs every morning at 7am without breaking.
We build on Zapier, Make, or n8n depending on volume and complexity. Zapier for small teams and simple flows. Make for the middle. n8n self-hosted when you need full control and the cost matters at scale. We keep the human in the loop on anything that touches a customer until the workflow has earned the trust to run unsupervised. By month three, the team has 8 to 20 hours back a week and the work they kept is the work they actually want to be doing.
- 20 yrsDoing this professionally, 40,000 hours of it
- 1,000+Entrepreneurs helped
- 1.6M+Views on 150+ how-to videos. Check the work before you buy
Industry benchmarks, not our client data
The gap ai & data has to close
- 4 hours A repeated weekly task nobody has looked at, still done by hand
- Under 1 hour The same task once it is automated, on the workflows where this works at all
Adoption among smaller businesses has roughly doubled in two years and still sits under 40 percent, against about 72 percent of large enterprises. The gap is not access to the tools. Everyone has the same models. It is that nobody has sat down and worked out which repeated task is worth automating first.
The honest scope: this works on well-defined, repetitive, text-and-data work, and it does not work on judgement calls or anything where being wrong once is expensive. You will see a 35 percent operating-cost reduction quoted around AI adoption. It is self-reported by the people who bought it, so treat it as a reason to run one pilot on one real workflow and measure it, not as a number for a business case.
Source: 2026 SMB AI adoption and automation reports (time savings and cost reductions are self-reported)
This is for you if
- You are doing the same task 50 times a week and a workflow could do it once
- Your team copy-pastes between tools and burns hours nobody is tracking
- You have tried n8n, Make, or Zapier and abandoned each because of one broken step
- You want a written list of what to automate first, second, third, not 'let us AI everything'
What it costs
No proposal theatre. These are the real numbers, and the full list for every service is on the pricing page.
- $190£150/hr Advanced Technical Workflow builds, AI integrations, custom tooling, and ongoing optimization. Most builds run 8 to 40 hours. Larger automation programs scope custom.
- $3.8k£3k to £15k Automation program scope A defined set of 5 to 15 workflows built and handed over with documentation and training. Most programs land at £5k to £8k. Heavier integrations push higher.
Need a number for your situation?
The prices above cover the standard engagement. If yours is bigger, messier, or does not look like any of that, tell us where you are and what you are trying to fix and we will come back with a straight price and a timeline. No lock-in, no "discovery phases", no surprises.
What this looks like when it works
- Your team gets 8 to 20 hours back a week, and you can name exactly which tasks they came from
- Lead intake, invoice processing, and ticket routing happen automatically and accurately, instead of getting buried in someone's inbox
- Your CRM and accounting system actually agree with each other, because the data flows in one direction without manual re-entry
- You stop hiring for clerical work and start hiring for the work that actually grows the business
- When a workflow breaks, you find out in 5 minutes from an alert, not in 3 days from a customer complaint
How we approach ai automation
The handful of principles that decide what we do and what we skip.
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Map before you build
Half a day with the team to find the tasks worth automating. Most automation fails because it automated the wrong thing.
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Spreadsheet first
If a Google Sheet and a Tuesday-morning habit solves it, we use that. Automation when the sheet runs out of road.
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Human in the loop until trust is earned
AI drafts, humans approve. We do not let a model send a customer email unsupervised on day one.
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Document so it outlives us
Every workflow has a one-pager: what it does, what triggers it, what to do when it breaks. You own it.
Questions owners ask before they commit
Isn't automation just a way to replace my team?
The opposite. We automate the repetitive drudgery, the copy-paste, the chasing, the data entry, so your people spend their hours on the work that actually needs a human. It frees them, it does not replace them.
How do I know what's even worth automating?
We start with your week, not a tool. We find the 3 to 5 places where work repeats, then automate only those. Some get a custom workflow, some get a spreadsheet and a habit. We use AI only where it earns it.
What if it breaks when I'm not looking?
We build it to fail safely, with checks and a handover so your team can see what is running and fix it. The first weeks include tuning, so it settles before you rely on it.
How we compare to the alternatives
The honest sales argument. We will not pretend the other options do not exist.
Doing it yourself
- You and your team learning every platform from scratch
- The work eats nights and weekends
- Hard to tell what is actually working until you have burned the budget
- One channel at a time because you cannot run them all yourself
- Pricey mistakes you eat alone
With Mujgos
- An operator who has actually shipped this work for paying clients
- Plain-English plan, plain-English reporting, no PDFs to interpret
- Fixed scope, real deadline. No 12-month contracts
- Decisions in 48 hours, not 4 weeks
- You keep the keys to every account, tool, and asset
Typical agency
- Junior staff in a process they cannot change
- Dashboards that confuse instead of clarify
- 12-month contracts and cancellation clauses
- Cookie-cutter playbooks they run on every client
- Padded retainers that grow quietly over time
How working with us actually goes
No 12-month contracts, no jargon, no lock-in. You pick what you need, we do the work, and you keep the keys.
- 01
Diagnose
A free 30-minute call. We figure out where you really are and what the next dollar of effort should go to.
- 02
Plan
We write the next 90 days with you. What to do first, what to skip, what to spend. So you stop guessing on Monday.
- 03
Build
We do the work. Fast and on a fixed price, not on hours billed.
- 04
Grow
Ongoing playbooks and a Slack thread or call when you're stuck. You run the business. We're the brain you call when something is off.
More inside AI & Data
- AI for Marketing Use AI for the marketing work that repeats. Skip the rest.
- Data & Analytics Five numbers in your inbox on Monday morning. Not a 12-tab dashboard nobody opens.
- Machine Learning Consulting Find out if you actually need ML before you spend a fortune building it.
- Conversational AI Build a chatbot only when it earns its keep. Most don't.
Ready when you are.
Pick the offer that fits. We'll meet you there.