Staff use AI on the side, but without shared rules.
Offer: AI process check
Where can AI genuinely save work in your company?
AI does not automatically save work just because a tool gets introduced. It helps where recurring tasks, existing data and clear decisions come together. An AI process check shows which workflows are suitable, which data is missing and which first workflow makes sense. The goal is not a large AI project but a concrete entry point with visible benefit.
Find recurring processes that really cost time.
Review product data, enquiries, emails, PDFs and internal knowledge sources.
Select and prioritise a first sensible AI workflow.
Direct answer
What is an AI process check?
An AI process check is a structured review of existing workflows, data sources and recurring tasks. The aim is to find where AI or automation genuinely helps in your company. Tools are not chosen first — real bottlenecks are examined: manual searching, recurring enquiries, scattered product data, PDF documents, email processes, shop data, internal knowledge sources and handovers between systems.
Many AI projects fail not on the technology but on the wrong entry point. If the first use case is too large, too vague or too poorly prepared, AI stays a test without effect.
The problem
Many companies test AI but don't solve a real workflow.
The interest is there. The concrete benefit is not — not because AI doesn't work, but because the entry point is missing.
Managing directors know AI matters, but not where to start.
Processes are half manual and half digital.
Product knowledge sits in PDFs, shop pages, emails, spreadsheets and people's heads.
Enquiries get answered in a similar way again and again, but by hand every time.
Data gets copied from one system into another.
Nobody knows which process should be automated first.
Am Ende gibt es viele Ideen, aber keinen produktiven Workflow.
Areas reviewed
Which areas does 10LYNNDALE examine in the AI process check?
Not every area is relevant. In the initial conversation we narrow down where the biggest effort arises in the company.
Product data
Is product information complete, unambiguous and machine-readable?
Technical enquiries
Which customer questions keep coming back and cost time?
PDFs and data sheets
Which information sits only in documents and is hard to use?
Email processes
Which messages are sorted, answered, forwarded or evaluated by hand?
Internal knowledge search
Where do staff search for the same information again and again?
Shop, website and product pages
Which content could be structured better, updated or generated from data?
CRM, ERP or inventory management
Where is data transferred by hand or maintained twice?
Support and sales
Which processes repeat and could be prepared in advance?
How it works
How does the AI process check work?
AI only saves work when the process has been understood first. The check follows a clear sequence.
Process conversation
Which processes regularly cost time? Where do follow-up questions, waiting times or copy-and-paste arise?
Reviewing the existing data
Product pages, data sheets, PDFs, emails, spreadsheets, FAQs, shop data or internal documents are reviewed.
Assessing what can be automated
Not every process is suitable. Repetition, data quality, risk, benefit and feasibility are assessed.
Selecting the first use cases
Out of several ideas, one to three realistic starting points are selected.
Prioritisation
Which solution delivers benefit quickly? What has to be tidied up first? What is too large for the start?
Recommendation for the first workflow
The result is not a general AI plan, but a clear recommendation for the first workflow worth starting with.
Assessment
How do you recognise a good AI use case?
Not every workflow suits AI. That is exactly why it gets checked first.
Poor use case
Too vague, too rare, too risky or dependent on knowledge that isn't documented anywhere.
- ✓
The process occurs regularly.
- ✓
The task costs measurable time.
- ✓
Existing information or data sources are available.
- ✓
The result can be checked by a person.
- ✓
The process has clear boundaries.
- ✓
Errors would be controllable.
- ✓
The benefit is visible to staff.
- ✓
The solution can start small.
- ✓
The data basis is sufficient or can be prepared.
Example
From a vague AI wish to the first workflow.
Starting point
A technical retailer wants to "do something with AI".
- ·Viele Kunden fragen nach passenden Produkten.
- ·Staff search PDFs and old product pages.
- ·Answers are written by hand.
- ·Product data is inconsistent.
- ·Some details only appear in the data sheet.
Assessment
Too early
A fully automatic sales agent. Data basis unclear, risk too high.
Sensible entry point
An enquiry assistant that prepares draft replies. A staff member checks and sends.
First: structure important product information better.
First workflow
- 1Anfrage erfassen.
- 2Produktbereich erkennen.
- 3Find the relevant data sheets and product pages.
- 4Suggest follow-up questions.
- 5Antwortentwurf vorbereiten.
- 6A staff member checks and sends.
The outcome
What results does the AI process check deliver?
The check does not end with a general list of ideas. It shows where you can sensibly start.
Prioritised list of sensible AI use cases.
Assessment of which processes are suitable and which are not.
Notes on missing data or unclear structures.
Recommendation for the first small workflow.
Assessment of effort, risk and benefit.
Proposal on which data has to be prepared first.
Clear next steps for implementation or a pilot project.
Optional proposal for the technical implementation.
Common mistakes
Why many AI projects in mid-sized companies never start.
A tool gets bought first
The tool then looks for a use case, instead of the other way round.
The first use case is too large
Effort, risk and dependencies outweigh the possible benefit at the start.
The data basis is unclear
AI can only be as good as the data it accesses.
Nobody has documented the real workflow
What is supposed to be automated isn't described clearly enough.
Staff are meant to use AI, but there are no rules
Everyone does something different. No shared benefit emerges.
The solution stays a test outside daily work
No result that gets used in normal operation.
There is no clear review step
Errors go unnoticed or arise uncontrolled.
IT, sales and management look at different problems
There is no shared priority and no clear project goal.
AI is discussed, but no concrete bottleneck is solved
Plenty of discussion, no productive workflow.
Why 10LYNNDALE
Not an AI workshop. A look into the digital engine room.
10LYNNDALE doesn't look at the tool first, but at the workflows, data and friction points in the company. The focus is on product data, website, shop, data sheets, email enquiries, internal search, inventory management, SEO, feeds and recurring work. That is exactly where it is decided whether AI can help in practice.
10LYNNDALE doesn't come from the classic agency world, but from running technical websites, shops and product data. AI is therefore not treated as a detached tool, but in the context of data, systems, website, product knowledge and daily work in the company.
"AI only becomes useful once it is connected to existing knowledge and real processes."
At a glance
What you receive.
The AI process check is clearly limited and not a large project. The goal is an affordable, concrete entry point.
A short preliminary call to narrow the scope.
Review of one selected process area.
Review of existing data sources.
Analysis of typical manual tasks.
Assessment of possible AI use cases.
Prioritised recommendation.
Proposal for a first workflow.
Notes on necessary preparatory work.
Optional: implementation of the first workflow by 10LYNNDALE.
Suitable cases
Who is the AI process check for?
Technical retailers.
B2B shops with products that need explaining.
Manufacturers with digital product data.
Companies with many PDFs, data sheets or product variants.
Small teams with recurring enquiries.
Companies testing AI without a clear process.
Companies with a shop, website, product data, CRM, ERP or inventory management.
Industrial supplies, occupational safety, traffic safety, reflective films, machine accessories, spare parts, technical films, construction supplies, fastening technology, packaging technology, electrical components.
For context
Who is the check not intended for?
Companies that only want a general AI talk.
Companies that don't want to show real workflows.
Companies expecting a fully automatic agent straight away.
Projects without access to product data, documents or example processes.
Companies that only want AI-generated text short-term.
Very simple processes without recurring effort.
Why now?
Why a small start beats a large AI project.
Many companies sit between interest and uncertainty. AI feels important, but the concrete benefit is often unclear. A large rebuild is usually the wrong start for that.
Many companies don't need an AI strategy. They need one workflow that actually works. A small, clearly bounded process that shows whether AI really helps day to day is the better start. That is exactly what the AI process check is for: check, narrow down, prioritise and start sensibly.
Contact
Find the first AI workflow worth doing.
If you know AI will play a role in your company but have no clear entry point yet, the AI process check is the right first step. 10LYNNDALE examines concrete workflows, existing data and recurring tasks. The result is not a general strategy but a clear recommendation for the first workflow you can implement.
FAQ
Frequently asked questions
What is an AI process check?
A structured review of existing workflows, data sources and recurring tasks. The aim is to find where AI or automation genuinely helps in your company. Tools are not chosen first — real bottlenecks are examined.
Is this an AI workshop?
No. A workshop conveys general knowledge about AI. The AI process check looks at concrete workflows, existing data and recurring tasks in your company. It ends with a recommendation for a first workflow you can implement — not a slide deck.
Which processes get reviewed?
Typically areas where staff regularly spend time on similar tasks: answering product enquiries, searching data sheets, transferring information out of PDFs, sorting emails, copying data between systems or searching internal knowledge sources.
Which area makes sense depends on the company. That is narrowed down in the initial conversation.
Do I already have to know which workflow I need?
No. That is exactly what the check is for. It turns vague AI ideas into concrete use cases. Many companies don't need an AI strategy. They need one workflow that actually works.
Do we already need clean product data for this?
No, that is not a prerequisite. The check examines exactly that, among other things: whether and how well existing data can be used. If the data basis needs tidying up, that is named as necessary preparatory work.
Do I only get an analysis, or the implementation as well?
The process check ends with analysis, assessment and a prioritised recommendation. You can implement the first workflow yourself, hand it to your team, or commission 10LYNNDALE. You decide after the check.
Is the check suitable for small companies?
Yes. The check is explicitly meant for small and medium-sized technical companies. No large project budget needed. The best entry point is rarely the biggest project.
What happens after the process check?
You have a clear recommendation for a first AI workflow worth doing. Either you implement it yourself, or 10LYNNDALE handles the technical work. Either way you have a concrete next step instead of another open question.