Data
Which data exists, where it is, with what quality and continuity. A valid use case can fail on incomplete data: better to know before investing.
AI Assessment
You want to bring AI into your company but don't know which process to start from? Seika Innovation's AI Assessment analyses your processes, quantifies where artificial intelligence delivers a measurable return and hands over a prioritised roadmap, with the first quick wins already implemented. Understand first, then act.
Seika Innovation's AI Assessment is a structured analysis, typically lasting 4-8 weeks, that evaluates a company's processes to identify where artificial intelligence and automation deliver a measurable return. The output is not a theoretical report: it is a prioritised roadmap of interventions, a training plan for the teams and the first AI quick wins, already implemented and measured.
Unlike approaches that start from the technology, the AI Assessment starts from the process: observation on the shop floor and in the office, real data, quantification of inefficiencies. The most expensive inefficiencies are often invisible because they have become operating habits: reports built by hand, slow approvals, documents processed one by one. The assessment makes them visible and turns them into an action plan with KPIs defined before starting.
Seika Innovation has applied this method in over 60 companies in 18 months, across manufacturing, logistics, construction, healthcare, pharma, finance and retail, from €1 million to over €5 billion in revenue, mapping more than 200 processes.
The evaluation rests on four axes. The score is not a grade: it is there to decide where to start and what to postpone.
Which data exists, where it is, with what quality and continuity. A valid use case can fail on incomplete data: better to know before investing.
How workflows really run, with what waiting, rework and manual steps. This is where the cost of inefficiencies is measured.
What the people who will use the tools can already do, by role. Adoption is the most frequent bottleneck, not the technology.
Which AI systems are already in use, with what rules and responsibilities, and what is needed to stay within the obligations of the EU AI Act.
The engagement follows four phases, from people to processes to the first implementations.
01
Focus groups with the teams, data collection and direct observation of real workflows. The goal is to understand how the company really works, not how procedures describe it.
02
AS-IS process mapping with process mining techniques, comparison with the TO-BE and economic quantification of inefficiencies: waiting, manual steps, rework, duplicated activities.
03
Identification of bottlenecks, repetitive activities that can be automated and inadequate tools. For every AI use case the expected return is estimated: only what has a measurable impact enters the roadmap.
04
Prioritisation with an impact/effort matrix and objective scoring (business impact, time, cost, complexity, change management). Role-based training plan on Copilot 365, Power BI, Power Automate and generative AI. Development of the first quick wins (0-3 months) with KPIs monitored from day one.
Reply within one working day, then a 30-minute call with no obligation.
Clients
60+
Manufacturing, healthcare, logistics, finance, retail. From €1M to €5B+ in revenue.
Training
30+
Copilot 365, Power Automate, Power BI. Hands-on training, not theory.
Processes
200+
AS-IS mapping with process mining and economic quantification of inefficiencies.
Efficiency
80-90%
Waiting, manual steps and rework: that is where capacity is recovered.
Manufacturing
Communication with 1,100 suppliers automated, -83% late deliveries.
Automotive
Approval cycle redesigned with process mining on 1,298 cases, average time from 4 days to 1.
Planning
Predictive demand models for a company with €80M in revenue, stockouts anticipated by 4 weeks.
Compare frequency, available data, exceptions and control work. A conscious choice distinguishes AI, rule-based automation and data analytics, and defines how to verify the result.
Read the checklist for choosing which processes to automate (in Italian) →FAQ
01
In commercial practice they mean the same thing: an evaluation of how ready a company is to use artificial intelligence on its own processes, and of where it pays to start. Beware of a namesake: the AI Assessment Scale is an educational framework that measures students' use of AI, and has no relation to this service.
02
Typically 4 to 8 weeks, depending on the size of the company and the number of processes analysed. The first quick wins are up and running during the engagement itself.
03
No. The analysis starts from observing real processes in the field. Where data is missing, the assessment also defines how to start collecting it.
04
The company receives a roadmap it can execute on its own. Seika Innovation can support the implementation of the projects and the training of the teams, but there is no obligation.
05
Yes. Seika Innovation has supported over 60 companies from €1 million to over €5 billion in revenue. The method adapts to scale: for an SME the assessment focuses on the 2-3 processes with the highest impact.
06
Yes. Italy's hyper-depreciation for 4.0 capital goods and regional grants cover investments in innovation and digitalisation. Seika Innovation helps identify the opportunities and prepare the documentation.
07
On site in more than 20 provinces of Northern Italy across Veneto, Lombardy, Emilia-Romagna, Trentino and Friuli, with headquarters in Conegliano (Treviso). Analysis and follow-up continue remotely.
Seika Innovation
The AI Assessment measures the hidden potential in your processes and defines how to unlock it. Over 60 companies have already done it.
Request the AI Assessment