Before we build anything, we map what is actually broken.
The Operational Automation & AI Readiness Diagnostic. Two to three weeks with a senior technical lead, your operations people, and your existing systems. You end with a workflow map, a ranked list of what is worth automating, an honest read on whether your data is ready, and a costed implementation path.
You can take that document to any vendor. Most clients don't.
What It Is
Why it exists
Most automation projects fail before a line of code is written. Not because the technology is wrong, but because nobody mapped the workflow properly, the data was not ready, or the wrong process was automated first.
The four questions it answers
- Where is the operation actually losing time, accuracy, control, and visibility?
- Which of those problems is worth solving first?
- Is your data in a state that supports what you want to build?
- What would implementation realistically cost, in what sequence?
Who it is for
SMEs and corporates with manual workflows, disconnected systems, ERP bottlenecks, document or order processing problems, reporting delays, or an AI idea that has not yet been tested against reality.
What You Receive
At the end of the engagement you receive a written diagnostic document containing:
- A workflow and pain-point map of the processes reviewed
- An analysis of where manual work and rework are concentrated
- The automation opportunities, ranked by value and complexity
- Data readiness notes — what is usable, what needs structuring first
- Integration risks across your existing systems
- Priority use cases, with a recommendation on what to do first
- A recommended implementation path with estimated build phases
- An optional implementation proposal
How It Runs
Discovery
Structured sessions with the people who run the process, not only the people who manage it. We review the systems in place and how data actually moves between them.
Analysis
We map the workflow, identify where time and accuracy are being lost, assess data readiness, and test the automation opportunities against what your systems can support.
Recommendation
We present the findings, the ranked priorities, and the implementation path, with estimated phases and costs.
Scope is defined before we start: a set number of sessions, systems reviewed, and workflows assessed.
Price
Depending on sector, complexity, the number of systems reviewed, and the level of senior involvement.
The price stays visible because hiding it produces unqualified enquiries, which is the exact problem this page is built to prevent.
Who It Is NOT For
The diagnostic is not:
- A consultation or proposal exercise
- The right fit if you already know exactly what you want built and need pricing
- Right for teams with no budget allocated for implementation
- For exploring AI ideas rather than an operational problem
If that is where you are, the case studies below are probably more useful than a call.
1,500 orders a day, arriving by email, keyed in by hand
The problem
A B2B FMCG distributor received around 1,500 purchase orders every day, almost all as email attachments, with most arriving in a spike before the afternoon cut-off. Multiple people did nothing but key them into NetSuite. Any delay put next-day delivery at risk, and growth meant hiring more people to type faster.
What the diagnosis found
The bottleneck was not order creation. It was that orders arrived in multiple different formats, product names did not match the master data, and nobody could tell which orders were at risk until the cut-off had passed.
What we built
Email capture through Microsoft Graph, extraction from PDF, Excel, and HTML attachments, client matching by sender and subject, SKU matching against the master product database using order history, a confidence score on every order, duplicate filtering, and validated insertion into NetSuite.
This is what a properly diagnosed automation looks like.
Request a Diagnostic
Tell us a bit about your operation so we can confirm this is the right fit.