AI Consulting & Implementation

Most AI projects never reach production. Ours do.

Many organisations start with enthusiasm and end up with a demo that changes nothing. We work the other way around: we start from your processes, pilot under control, and scale only what shows measurable value. This page describes what a real implementation looks like.

Book a discovery call

30-60 min. We see if AI is the right tool for your organisation.

Case study

What the partnership looks like in practice

Medisprof Cancer Center, a private oncology clinic in Cluj-Napoca, Romania, started the collaboration with a single project: a chatbot answering patient questions.

The chatbot worked, and the trust it built opened the next steps: an AI education programme for staff, an internal AI usage policy, one-to-one mentoring for employees, and custom solutions built on the clinic's own processes.

One month after the training programme, participants reported saving between 1 and 8 hours per week, depending on their role, but also unlocking business value by using AI for new tasks, improved quality and less errors. The collaboration did not start with a large signed package. We delivered one project, measured it, then expanded what worked.

From one chatbot to full adoption

Medisprof Cancer Center

Up to 8 hours saved per employee per week

Patient chatbot, two-level AI training, internal AI policy, mentoring, custom builds.

What you get

Five concrete outcomes

Process mapping and AI strategy

A clear map of the processes where AI produces measurable value, with priorities argued and documented.

High-value use-case identification

A validated list of initiatives with high ROI and controlled risk, built in workshops with your team.

Prototyping and pilot projects

A working pilot, tested with real users and with its impact measured.

Optimising existing AI systems

More precise responses and lower costs for the AI solutions you already run, through prompt and context engineering.

Adoption and scaling framework

Policies, working practices and internal training. An organisation ready to work with AI for the long term.

How we work

Six steps, each ending in a concrete deliverable

Discovery and alignment

We map your business context, challenges, and current level of AI adoption.

Deliverable: A short alignment document: objectives, value areas, success criteria.
Needs-identification workshops

Sessions per department to find the workflows where AI reduces effort or raises quality.

Deliverable: A concrete list of candidate use cases, by department.
Evaluation and prioritisation

Each use case is assessed for impact, feasibility, risk, and time to value.

Deliverable: 2-3 use cases selected for piloting, with the reasoning documented.
Experimentation and piloting

We build working prototypes and test them in controlled environments with real users.

Deliverable: A usable pilot, with measured impact and documented user feedback.
Launch and integration

Solutions that prove results get scaled: technical integration, usage policies, internal training.

Deliverable: The solution in production, with the policies and training that sustain it.
Expansion and continuous optimisation

We document working practices, standardise processes, and map the next wave of use cases.

Deliverable: An internal AI adoption framework: stable, safe, scalable, plus the next-wave roadmap.

What a first engagement looks like

Start small, with a defined scope

A first engagement typically covers discovery, the needs workshops, and the prioritised use-case list: a defined scope with a clear deliverable, so you can judge the work before committing to a pilot. From there, each stage is decided on the results of the previous one.

Who this is for

We work well together if

You have repeatable processes and volumes that justify automation: institutions, healthcare, education, services.
You want measured, verifiable results.
Your team is willing to be involved: AI implementation is a project for the whole organisation.
You prefer to start small and expand what works.

Who this is not for

If the goal is a quick demo for a conference, or “AI implemented by Friday” without the team’s involvement, we are not the right partner. We work with organisations that want AI still in use after the we have left.

Return on investment

What the value looks like in numbers

Across delivered projects, participants report saving between 1 and 8 hours per week, depending on role and on the processes automated, but also unlocking business value by using AI for new tasks, improved quality and less errors. At team level that adds up to full working days recovered every month, measured through follow-up surveys one month after implementation.

Who delivers

A methodology tested in demanding environments

The founder, Ștefan Rusu, PhD in finance and AI (Summa Cum Laude), worked in the European Central Bank's Digital Transformation and AI Programme, contributing to large-scale AI solutions, operational chatbots, and the training of more than 400 of the bank's experts on AI use.

The training programmes were delivered during the founder’s time working at the European Central Bank. This does not necessarily constitute a public endorsement of AI Solutions or its services by the European Central Bank.

More about the founder

Organisations we work with