Many businesses have already brought artificial intelligence tools into their processes: ChatGPT, Claude, Copilot, automations with Make or n8n, internal knowledge bases, custom assistants and increasingly complex workflows. In most cases, the problem is no longer implementing AI. The problem is understanding whether everything that has been built actually works as intended. Technical consulting for AI workflows and systems helps businesses and professionals get clarity on their existing processes, identify inefficiencies, reduce operational risks and make their automations more reliable.
what I do
You run a business, lead a team or manage several projects on your own. You’ve heard about ChatGPT, Claude and AI automations for email, content and reports. Maybe you already use them, but not in a structured way — different tools for similar tasks, prompts written from scratch every time, no criteria for what is worth automating and what isn’t. The problem isn’t adopting the tools. It’s that without analysing the existing workflow, you risk adding complexity instead of reducing it: new tools on top of processes that are already confused, content generated without control, automations nobody knows how to handle when they stop working. This consultation is for anyone who wants to understand where AI brings a measurable advantage in their specific context — not in the abstract, not as a trend to follow, but in relation to how you work today and what costs you the most time.
the service
The analysis starts from how you work today: internal processes, tools in use, manual steps, existing automations, content produced, data handled and recurring tasks. The goal isn’t to add AI everywhere, but to identify where artificial intelligence can create real value, where it is instead creating operational noise, and which processes need to be simplified before they are automated. For each area I assess the maturity of the workflow, the dependencies between tools, the level of supervision required, the operational risks and the concrete impact on time, quality and the sustainability of the process.
Analysis of daily processes, manual steps, recurring tasks and the points where work gets stuck or duplicated. I identify which processes can be simplified, documented or automated without making the system more complex.
Review of the AI tools already in use, such as ChatGPT, Claude, Copilot, Make, n8n, Zapier, custom assistants or internal automations. I assess whether the tools are used consistently, whether they create real efficiency or whether they are creating dependencies that are hard to control.
Analysis of documents, procedures, reports, internal content and material produced or managed with AI support. I check quality, consistency, duplication, how up to date the information is and how reliable the sources used in the workflows are.
Assessment of how data is collected, aggregated and summarised. I identify where AI can reduce the work of first reading and organising information, but also where checks are needed to avoid errors, weak interpretations or output that can’t be verified.
Defining the points where human control, technical review or validation is needed before an output is used, published or delivered. The goal is to build more reliable workflows, with clear rules on what can be automated and what must stay under supervision.
how I work
I start by analysing the existing system: tools already in use, recurring tasks, existing automations, available documentation, team structure and the main operational bottlenecks. From there I assess where artificial intelligence is already creating value, where it can be introduced with a measurable impact and where it only risks adding complexity, dependencies or unnecessary costs. The result is an operational roadmap with priorities, issues, recommended tools and concrete guidance to make workflows, automations and AI systems more efficient, reliable and manageable over time.
Gathering the operational context: what the business does, the digital and AI tools already in use, current work processes, existing automations, known problems and the areas where the team feels it is losing time, quality or control.
A systematic review of processes, of the dependencies between tools and of the points where AI is involved or could be. I document bottlenecks, duplication, operational risks, repetitive manual tasks and areas that need human supervision.
Defining the order of the work: quick wins that can be implemented straight away, medium-term improvements, processes to simplify before automating, and areas to leave out because the cost, risk or complexity outweighs the benefit.
Delivery of a structured document with analysis, priorities and practical guidance. I distinguish between what you can manage yourself, what needs technical support and what should be monitored over time to avoid losing control, quality or sustainability.
real cases
What often comes up when workflows, automations and AI tools grow without structured management
Workflows built on Make, n8n, Zapier or similar tools that work until something breaks. There is no documentation, no explanation of the logic of each step, no operational responsibility and no guidance on what to do when an error occurs.
ChatGPT, Claude, Copilot or custom assistants used by different people for similar tasks, but without shared criteria. Each team member works with different prompts, methods and output, which makes consistency and quality hard to maintain.
Texts, reports, captions, presentations or internal documentation produced with AI but only checked at the end, when the time has already been spent. The risk is ending up with material that is formally correct but generic, inconsistent or not reliable enough.
Internal documents, procedures, project material and company information used as a basis for AI tools without periodic review. If the system works on duplicated, old or contradictory content, the output becomes less reliable too.
AI licences, automation tools, productivity software, APIs, plugins and integrations switched on over time without an overall view. The real cost of the system is often higher than it seems, especially when some tools overlap.
Client information, contracts, internal data, credentials or confidential material copied into AI tools without clear policies, anonymisation or control over how the data is processed. It is one of the most delicate points, especially for businesses and professionals who handle confidential information.
€690.00
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