Marketing agencies producing monthly reports
If your team still writes the first draft of every client report from a blank page, that's the workflow we replace.
AI workflows, not AI hype
Your team is wasting hours on work AI could already handle.
We turn reporting, lead handling, and follow-up into simple, reliable workflows — without breaking your process or risking bad outputs.
Built by a technical founder with 25 years of experience fixing systems that actually have to work.
Takes 15 minutes. No prep needed.
We'll identify one workflow worth fixing and show what it would look like.
workflow feed · livelive
09:14REPORTbrightside-march-2026 → review queue✓
09:13ENQUIRYalgarve-villa-€650k · profile extracted✓
09:13ALERThot-lead flagged · agent notified✓
09:11APPROVEcampaign-summary · awaiting human✓
09:10DRAFTreply-en-GB · 4 fields populated✓
09:08INPUTcampaign-data · 4 rows validated✓
›
Step 3 · Human review
1 draft awaiting approval
Nothing sent without sign-off
Practical AI systems for:
- Client reporting
- Lead handling
- Follow-up workflows
- Content production
- Internal knowledge search
- Admin-heavy processes
Who this is for
If your team does any of this manually, we should talk.
Estate agents handling inbound enquiries
If buyer enquiries sit in an inbox until someone has time to read them, you're losing serious leads to faster competitors.
Small teams dealing with repetitive admin
If the same email, summary, or follow-up gets written over and over, that's a system waiting to be built.
Why AI projects stall
Most AI projects don't fail because the AI is bad.
They fail because nobody turns the idea into a working system.
A team tries ChatGPT. Someone builds a quick Zapier flow. A few prompts get shared around. For a week it feels promising. Then the outputs vary, the workflow breaks, nobody owns it, and the business goes back to doing things manually.
That is the gap we fix. We design the workflow, build the system, add safeguards, and make sure it fits how your team actually works.
Failure mode 01
Tools without systems
A prompt is not a process. A workflow needs defined inputs, outputs, and ownership.
Failure mode 02
Inconsistent outputs
If the result is different every time, the team can't trust it — so the work quietly goes back to manual.
Failure mode 03
No clear ownership
When the prompt-author leaves, the workflow dies with them. That's a brittle system, not a business process.
Failure mode 04
Workflows that break quietly
Most AI experiments don't fail loudly. They just stop being used. Nobody announces it; it just fades out.
Why teams pick us
We build the system, not the slide deck.
A useful AI workflow needs more than a prompt. It needs clean inputs, predictable outputs, approval steps, error handling, and ownership. That's where 25 years of systems experience matters.
We build like engineers, not AI tourists
Most AI consultants know the tools. Fewer understand what it takes to make a system work in the real world: clean inputs, predictable outputs, approval steps, error handling, and a process your team will actually follow.
Start with one workflow
We don't sell strategy decks. We take one repetitive process — reporting, lead handling, follow-up — and turn it into something reliable. Big programmes can come later.
Humans stay in control
The first draft is automated. The final call stays with your team. Every workflow we build has explicit approval steps, logging, and escalation rules for uncertain cases.
Services
Start with one workflow.
Three core services built around the work that eats agency and property-business time. Pick the one that matches your pain.
See it working
Most teams are still doing this manually every week:
- pulling data
- writing summaries
- replying to leads
- chasing follow-ups
Here's what that looks like as a system:
A prompt can generate text. A system makes sure the right input goes in, the right output comes out, and a human checks the result before it affects your business.
Approach
How we work.
Same shape every time. Small scope, working system, clear handover.
1
Step 1
Find the right workflow
2
Step 2
Map how work actually happens
3
Step 3
Build the first controlled version
4
Step 4
Add safeguards
5
Step 5
Train the team and hand over
1
Step 1
Find the right workflow
2
Step 2
Map how work actually happens
3
Step 3
Build the first controlled version
4
Step 4
Add safeguards
5
Step 5
Train the team and hand over
Recent work
Recent projects from the practice.
A few of the systems we've shipped. AI built into the workflow, not bolted on at the end.
Marketplace for racket-sport gearLive
EpicRackets
An online marketplace for reselling padel, tennis, and racket sport gear. AI ran through the build itself — code, design, and the marketing automations behind listings, alerts, and follow-up.
AI-assisted build · Marketing automationepicrackets.com
Invoicing for the Polish marketLive
doFaktur.pl
An invoicing product built for the Polish market. AI sits in the customer-facing chat, helping users analyse their billing data and produce invoices that meet Polish compliance rules.
Customer-facing AI chat · Compliancedofaktur.pl
Crypto sentiment platformArchived
MarketCompass
A market-sentiment platform for altcoins. Pulled discussion from multiple sources and ran it through trained models that classify sentiment with around 70% accuracy — measured against labelled data, not vendor numbers.
Trained AI models · Web · Data—
One workflow at a time
Have a workflow that shouldn't still be manual?
Tell us the process. We'll show you what AI can actually do here, what it shouldn't touch, and what a working first version would look like.
Currently working with a small number of clients while building out systems.
Show me what to automate
Takes 15 minutes. No prep needed.