Processes
Manual activities, repeated steps, bottlenecks, waiting times, recurring errors and dependencies on single people. Without this map, any benefit estimate is guesswork.
AI consulting for companies in Italy.
Useful AI consulting starts from business processes, not from the model you pick. Faraday AI Studio reviews the work, the data and the systems already in place to find where artificial intelligence delivers a concrete advantage — and where a simpler solution works better. The outcome can be a roadmap, a priority use case, a pilot project or an integration plan. We are based in Rome and work with companies across Italy.
When AI consulting actually helps
- Repetitive tasks absorb hours of skilled work every week
- Teams use disconnected tools and the same information is re-entered several times
- Documents, contracts and archives hold useful information that is hard to retrieve
- Customer service keeps receiving the same requests with already known answers
- Some processes depend on a single person and stall when that person is unavailable
- The company wants to adopt AI but does not know which use case to start from
- Isolated internal experiments already exist, with no roadmap holding them together
- Management wants to understand costs, benefits and risks before approving an investment
What we analyse
The assessment looks at the company on six levels. It separates the problems AI can solve from those that come from how work is organised, which no model can fix.
Data
Availability, quality, structure, accessibility and ownership of data, plus the nature of the information handled. Data readiness decides which use cases are realistic now and which need preparatory work.
Systems
CRM, ERP, management software, databases, mailboxes, document archives, internal applications and available APIs. A use case is worth little if it cannot be integrated where people actually work.
People
Departments involved, responsibilities, existing skills, approval steps and the level of oversight required. The people who will use the tool take part in the evaluation from the start.
Value
Time absorbed, current cost, output quality, response speed, customer experience and decision-making capacity. For each use case we define how the effect on the process will be measured.
Risk
Handling of personal and confidential data, access security, tool permissions, logging, vendor dependency, model errors and, where applicable, AI Act requirements.
From the problem to the roadmap
Four phases in sequence: first we understand how the company actually works, then we decide what is worth building. Technology comes last, not first.
Discovery
Interviews with the departments involved, observation of real workflows, review of data and systems. At this stage we collect problems, waiting times, manual steps and dependencies — we do not propose a solution yet.
Roadmap
The use cases we found are ranked by expected value, technical complexity, risk, prerequisites and dependencies. The result is a reasoned execution sequence, including what must be in place before starting.
Pilot
One narrow use case, with KPIs agreed upfront, minimal integration with existing systems and a review of results together with the people who will use the tool every day.
Scale
If the pilot holds up, we move to stable integration, monitoring, access governance, team training, recurring running costs and continuous improvement cycles.
What the company gets
Depending on scope and depth, the engagement can produce documents your internal teams can also use on their own:
- Map of priority processes and their critical points
- List of identified use cases, with description and scope
- Value / complexity matrix to order the work
- Assessment of available data and the gaps to close
- Integration requirements against the systems in use
- Main risks and the level of human oversight needed
- KPIs and measurement method for each use case
- Roadmap with sequence, prerequisites and dependencies
- Proposal for a possible pilot with goals and validation criteria
- Preliminary estimate of the internal and external resources required
Not every project needs all of these documents: the scope is agreed before we start, based on how wide the picture to analyse is.
When the roadmap shows that building something makes sense, the next step is technical. Depending on the use case it can be a conversational assistant, automations between existing systems, agents that carry out multi-step tasks, or custom software. The work is delivered by a team that combines analysis, software development and AI implementation.
AI chatbots · AI automation · AI agents · Custom AI software · All services · The Faraday team
How we choose the use cases
Not every AI idea deserves an investment. Each use case found in discovery is assessed against explicit criteria, so the decision stays open to discussion and verification by management:
- How often the process repeats
- Cost and time it absorbs today
- Quality and availability of the required data
- Integrations needed and how feasible they are
- Operational, reputational and regulatory risk
- Level of human oversight required
- Real impact on the daily work of the teams
- Whether the result can be measured
- Technical effort and skills required
A high-value, low-complexity use case usually enters the roadmap first, but this is not an automatic rule: a more complex piece of work can take precedence if it unblocks the others or removes a significant risk.
When AI is not the best answer
Part of the job is discarding ideas that do not hold up. Flagging early where AI is not worth it avoids wasted budget and projects abandoned after a few months.
The process follows fixed rules
If a workflow always follows the same three conditions, traditional automation is simpler to maintain, more predictable and easier to audit.
There is not enough data
Without sufficient history, or with data that is inconsistent across sources, a machine learning prediction is unlikely to be reliable: fix the data first.
The process is not stable
If the rules change every week, automating before stabilising adds complexity and maintenance instead of reducing them.
Cost outweighs benefit
When the task is infrequent or the time saved is marginal, development, integration and maintenance do not pay for themselves.
The risk is disproportionate
For decisions with significant legal, health or financial impact, full automation is not appropriate: AI can at most support the person deciding.
The decision must stay human
Some judgements require accountability, context and relationship. Here the goal is to give better information to the decision maker, not to replace them.
Human oversight and accountability
In high-impact processes the design defines who approves, who validates outputs, under which conditions the system must stop and when a case must be escalated to a person. We also state which actions are deliberately not fully automated. On the data side we review the types of information handled, access rights, flows towards external services, hosting, tool permissions and logging. Where the use case requires it, the roadmap accounts for transparency, traceability and applicable AI Act requirements: these are design considerations, not a compliance certification.
References used
On site or remote
The two formats are not equivalent in every situation: the choice depends on how many people need to be involved, how observable the processes are from a distance and which systems have to be examined. They are often combined, starting on site and continuing remotely.
On site
Useful when you need to see the work as it happens and put departments that rarely talk to each other in the same room. It is the most effective way to surface informal steps that nobody has documented.
- Workshops with several departments at once
- Direct observation of operational processes
- Interviews with the people doing the work
- System review together with those who administer them
- Training sessions and shared decisions
Remote
A remote engagement can keep a high level of depth when processes, documentation and the people involved can be analysed effectively at a distance. It suits distributed teams and phases that do not require physical presence.
- Discovery and structured interviews over video calls
- Process review on shared documentation
- Analysis of documents, record layouts and system exports
- Roadmap building through working sessions
- Follow-ups and digital workshops between phases
Cost depends on the number of processes analysed, the people and departments involved, the complexity of the systems to review and whether a pilot is developed. A focused first assessment can be completed within a short timeframe, while work spanning several departments, data sources and integrations requires deeper analysis. Scope, duration and investment are agreed before we start.
AI consulting across Italy
Faraday AI Studio is based in Rome and works with companies across Italy. Assessment, design and roadmap work can be run remotely, while workshops, training and operational sessions can also take place on site when the project calls for it.
We work with organisations spread across the country without inventing artificial differences between one city and another: the engagement is built around processes and business needs, not around location.
Frequently asked questions
What does AI consulting actually do?
It reviews the company's processes, data and systems to find where artificial intelligence can produce a measurable benefit, ranks the use cases by priority and defines how to bring them into production. It is not a presentation about available technologies: it is analytical work on how the company operates today.
How do you tell whether a process suits AI?
We look at how often it repeats, the time and cost it absorbs, the quality of available data, the integrations required, the associated risk and whether the result can be measured. If even one of these is missing, we say so before proposing anything.
What does the company receive at the end?
Depending on the agreed scope: a map of priority processes, the list of use cases, a value/complexity matrix, a data assessment, integration requirements, risks, KPIs, a roadmap and a possible pilot proposal. These documents are designed to be usable internally too.
Do we need an in-house AI team already?
No. In most projects we work with process owners and the existing IT function. If technical skills are already available in-house we involve them; otherwise the roadmap states which roles are needed and at which stage.
Do we need perfectly structured data first?
No — data evaluation is part of the assessment. We check what exists, in which format, who can access it and how reliable it is. If a use case needs preparatory data work, that enters the roadmap as an explicit prerequisite.
How long does an AI consulting engagement take?
It depends on the number of processes to analyse, the people involved, the systems in scope and the depth required. A focused assessment on a single area is relatively quick; work touching several departments and systems takes longer. We estimate duration after the first call.
How much does it cost?
There is no fixed price list. Cost is determined by the number of processes analysed, the departments involved, the complexity of the systems and whether a pilot is developed. Scope and investment are defined before we start.
Does consulting include development?
They are separate activities. Consulting covers analysis, prioritisation and roadmap; a pilot is a narrow validation of a single use case; development and integration are follow-on projects, which can be delivered by us or by an internal team following the requirements we define.
How are data and privacy handled?
We review the types of data handled, the presence of personal or confidential information, who accesses what, where systems are hosted, which external vendors enter the flow, logging and tool permissions. These considerations guide design choices and must be validated with the company's privacy and security contacts.
Do you offer AI consulting across Italy?
Yes. Faraday AI Studio is based in Rome and works with companies throughout Italy. Activities can be organised remotely or on site when assessment, workshops or training require direct involvement of the teams.