The Pi School of AI programme is designed to solve business challenges using state-of-the-art AI technologies. Pi School controls risk exposure by operating with known resources within set times, ensures world-class expertise and techniques, and analyses existing products/APIs to determine initial performance levels.

The Pi School of AI rapid prototyping method – AI Sprint – consists of 4 steps:

1. Defining project scope through input/output data analysis.
2. Defining benchmarks: test protocols, data, and quantitative metrics in week 1.
3. 8 weeks of Agile Development with 1-week sprints, in close collaboration. Each sprint delivers an evolved version based on feedback.
4. Drafting a final report from week 5, presenting analysis results.

For each project of the School of AI, which we call AI Sprint, the Pi School team will deliver a report with the data analysis results, as well as Python scripts and algorithms implemented using standard data analysis and Machine Learning technology stacks and specialised software libraries. A final technical report will summarise the experimental work, performance metrics, and results.

The client will provide specific resources (e.g., detailed historical data on…). The quality of the final challenge report is highly dependent on the correctness and quality of the provided resources/data.

All project outputs (report, prototype, source code) become the client’s intellectual property. Future developments are expected to become proprietary technology, and project results will remain confidential under an NDA. All publications require prior authorisation. Intellectual property produced by Pi School, its mentors, and participants is fully transferred to the client.

The agreement is formalised thanks to a template that we use for our contracts that includes an explanation of our commercial offer and a “challenge brief” that defines the main points of our offer and the challenge: Problem and Solution: formulation of the challenge, description of the Tasks, resources and their estimated ‘effort’ in weeks, available data, points of attention, confirmation of the transfer of intellectual property, deliverables, identified opportunities and profiles of our team that will work on the challenge. To complete this challenge brief, we rely on our meetings and the client’s information via the “Project Information Request”. Or you can book a call.

The challenge brief provides all technical details of the approach. It outlines the problem and solution, initial backlog based on Scrum methodology, the scope of the challenge and deliverables, data requirements, identified attention points, identified opportunities, and the Pi School and Sponsor teams.

Our rigorous selection process ensures only the top 10% of 300 highly qualified applicants join our team, including bright graduate data scientists with AI expertise and experienced software engineers pivoting into AI. Furthermore, our team benefits from continuous mentoring and coaching by our expert AI team, ensuring they apply world-class techniques to even the most complex AI projects.

We also have a custom development project division for full product rollout, with sample projects including Pinocchio, the world’s first AI puppet. If your current projects are beyond the initial prototyping phase and you are focusing on building out complete solutions, Pi School frequently partners with Humans.tech for full-scale development and rollout. They are a capable team and might be able to provide the additional manpower you require. We would be happy to make an introduction to their CEO if you think it could be beneficial.

We completely understand.
Many of the companies we work with started out in a similar position, recognising a resource gap, but not yet ready to involve external partners.
Our approach isn’t about adding workload or handing over control. It’s about enhancing your internal capabilities, with AI talent that works with your team, not around it.
When you’re ready to explore what AI can do for your business with minimal friction and maximum learning, we’ll be here.

We ensure the project works through a collaborative, iterative process:

1. Challenge Brief: We build a detailed “challenge brief” based on your specific needs.
2. Weekly Meetings & Feedback: We hold weekly meetings to show you our progress and gather your feedback. This provides 8 opportunities to refine and improve the solution throughout the 8-week prototyping challenge.
3. Experimentation & Iteration: AI projects inherently involve experimentation. We learn from what works and what doesn’t, continuously refining the model to maximise success and improve accuracy.
4. Defined Inputs & Outputs: We work with you to clearly define the inputs, desired outputs, and style. This allows us to continuously refine the model to meet your qualitative expectations, even though a definitive “accuracy score” for creative outputs isn’t always possible.

Our solutions are built on state-of-the-art AI technologies. Our expertise is validated by multi-million euro investments from prestigious organizations like the European Commission and the European Space Agency, who trust us to solve complex, state-of-the-art problems.

The Service includes:

• Technical and scientific consulting from Pi School’s AI engineering team.
• Ad-hoc selection of two highly skilled AI engineers for the project.
• Creation of a dedicated AI team of 5 people (1 Project coordinator, 1 Lead AI scientist, 1 Senior AI scientist, 2 selected AI engineers).
• An 8-week timeboxed prototyping challenge.
• AI development by Pi School’s AI engineers, trained in “Agile for AI.”
• Mentoring and coaching by their expert AI team.
• Weekly project meetings.
• Intellectual property rights on all project outputs (report, prototype, source code).
• Social media activity related to the Challenge (with client consent) to enhance the company’s innovation image, including posts and a final “Pitch Day” event.
• A final presentation and networking event (“Pitch day”) at Pi School’s venue.

Yes, we can ensure the engineer is upskilled and ready to transition within the company at the end of the challenge.

We sometimes accept one member of the client’s company into the team, but this member should fulfil some knowledge requirements. Your employees can be involved in the team’s activities daily or, depending on availability, for at least eight hours to facilitate project adoption post-completion.

Yes, support with a Senior AI scientist for in-depth fine-tuning of the AI prototype during the month following the challenge is available.

The prices (excluding VAT) are:

• Base Package: 30,000 €
• Learning-by-doing immersion: 5,000 € per employee. 

Yes, fellows receive a grant worth €12,500. We charge a fee even when companies provide employees as fellows because of the significant value they gain: experience working with top mentors on a process proven over 100 times, solving real problems with state-of-the-art AI. This experience helps fellows skyrocket their careers, with some having worked for OpenAI, Google, and some having founded multi-million euro companies. Companies pay a fee because they receive all this value, and €5K is significant.

Payment is due in two installments: 50% at the beginning of the session and 50% at the end of the project.

We help you discover where AI can deliver measurable value in your business with our 2-week discovery AI Opportunity Mapping and define a prototype you can build fast.

Week 1: Understanding & Ideation

• Kickoff Meeting (1h): Align on business context, goals, and current operations.
• Asynchronous Research: We review available processes, data, and workflows.
• AI Opportunity Workshop (2h): Co-create a list of potential AI applications (including automation, prediction, personalization, etc.).
• Prioritization Matrix: Feasibility vs. Impact assessment to shortlist 1–2 MVP directions.

Week 2: Validation & Scoping

• Technical Feasibility Review: Our team assesses data availability and integration needs.
• Prototype Scope Definition: What we’d build in 8 weeks: inputs, outputs, models, constraints.
• Delivery & Business Value Framing: How we’ll measure success and ROI.
• Final Presentation (1h): We deliver a 5- to 7-page Discovery Report & Offer of the proposal.

Final Deliverable: Discovery Report

• Executive Summary
• Prioritised AI Use Cases
• Selected MVP Scope (with timeline, roles, assumptions)
• Tech Stack & Integration Needs
• Expected Business Impact
• Level of effort required from the client.
• Optional: Funding fit (if grant-backed).

We run three/four sessions per year and take 4-5 challenges each. The next session is in mid-October. We typically run sessions quarterly, and February is a strong possibility for the next one, but we don’t know exactly when and if we will have availability. We can secure one of the 6 projects per session, for 4 sessions a year.

We understand the concern about investing in a prototype and the desire for transparency regarding potential future costs and scenarios. Our 2-week “AI Opportunity Mapping” program is designed to address this. This discovery phase helps you:

• Determine Prototype Viability: Before committing to the 30K prototype, we work with you to discover where AI can deliver measurable value and define a prototype that can be built quickly. This initial mapping helps assess if the prototype is likely to yield desired results.
• Identify Future Scenarios and Risks: Through the “AI Opportunity Workshop” and “Prioritization Matrix,” we co-create a list of potential AI applications and assess their feasibility and impact. This helps in understanding various outcomes beyond the prototype and the potential risks involved.
• Scope Full Product Development: The “Prototype Scope Definition” outlines what would be built in an 8-week prototyping challenge, including inputs, outputs, models, and constraints. This informs the potential scope for full product rollout.
• Outline Business Value and ROI: We define how success will be measured and the expected Return on Investment (ROI), providing a clearer picture of the value generated at each stage.

To address concerns about managing budget expectations and avoiding surprises, our 2-week “AI Opportunity Mapping” program also includes a detailed report with prioritized AI use cases, selected MVP scope with timeline and roles, tech stack, integration needs, and expected business impact. This report provides a clear understanding of the project’s trajectory, allowing for more transparent planning and budgeting for all involved stakeholders, thus minimizing surprises and ensuring budget alignment. This proactive approach aims to minimize surprises and provide a clear roadmap for your AI initiatives, addressing concerns about budget alignment and potential future investments.

Our “AI Opportunity Mapping” program includes a Technical Feasibility Review specifically for this purpose. Our team evaluates your data availability and integration requirements to determine if your solution needs both hardware and software, or if it can be achieved leveraging existing solutions or partnerships. This review also identifies the most suitable and efficient AI models or technologies (e.g., GPT-4, Mistral, or a custom open-source Large Language Model) for your prototype, while also considering new and emerging AI advancements.