Common problems
Staff spend 30–50% of their time on repetitive tasks
Data is scattered across tools and hard to sync
Manual reporting wastes time and introduces errors
How MADIAD solves it
How an automated process runs
From the moment work appears to the moment it is done — and where people keep the wheel.
Flow diagram of an automated process, six steps from trigger to logging.
Something happens
- 01
Trigger
On a schedule, or the moment an event lands — a new order, a submitted form, a payment clearing, a file arriving.
- Schedule
- Webhook
- Inbound email
- New file
- 02
Pull data into one place
Fetched from the tools you already use and normalised, so the next step is not guessing at formats.
- Spreadsheets
- CRM
- Invoicing
- Inventory
- 03
Check and reconcile
Compare sources, surface gaps and missing data. This is the step people skip because it is dull.
- Reconcile
- Deduplicate
- Catch missing fields
- 04
Decide by rule
Anything with clear rules runs as rules — fast, cheap, predictable. AI is called only where language or context genuinely needs it.
- Conditions
- Branching
- AI where needed
- 05
Execute
Write records, send notifications, generate documents, update systems. Anything touching money or going out to a customer asks a person first.
- Write data
- Notify
- Generate reports
- 06
Log and alert
Every run is kept. When it breaks someone knows that day, rather than finding out a week later through wrong numbers.
- Audit log
- Alerts
- Replayable
Done, with a trail
Every step is logged. When something breaks you know which step, rather than retracing the whole chain.
What automation covers
Repetitive work goes to the machine; judgement stays with people.
Spreadsheets, CRM, email, invoicing, internal chat, inventory. Data moves between them instead of being retyped from one into another.
The Monday morning report, month-end reconciliation, or triggered the moment an order lands, a form is submitted, or a payment clears.
Compare two sources and surface the gaps. People find this work dull and skip it; a machine does not forget.
Rule-based steps run as plain automation — fast, cheap, predictable. AI is called only where language or context genuinely needs it.
Every run is recorded. When something fails, someone knows that day rather than discovering it a week later through wrong numbers.
What you get
- Automated workflow running 24/7
- Monitor dashboard
- Process documentation
- Training + handover
What we need from you
- A description of the current process — who does what, where, in what order
- Access to the tools involved, and someone who knows the data inside them
- Someone on your side who can sign off that the result is right
What to know before you start
- Automating a messy process only makes it messy faster. The first step is always mapping it, and sometimes the conclusion is to fix the process before automating anything.
- We need access to the systems being connected. A tool with no API and no export is a real constraint, and occasionally a dead end.
- When a vendor changes their API, things break. That maintenance is a genuine ongoing cost, not a one-time build.
- This does not replace people where judgement or accountability is required. Machines take the repetition; people keep the decisions.