AI PROJECT: DIGITAL T LEVEL

This project is in partnership with Vasilij Nevlev who is the founder of AiGentic Lab.

Our Digital T Level students are putting their skills into practice with an exciting team project alongside Vasilij. Their challenge is to create an AI-powered chatbot that can help answer everyday transport questions, including queries about costs and timetables. Using information supplied by the college, students will develop the chatbot to provide clear and accurate answers, as well as recognise when human support is needed.

AiGentic Lab is supporting the project from initial planning through to final delivery. This includes providing the brief, success criteria, example questions and data sources, alongside a kick-off and requirements-scoping session. Their partnership also provides mentoring on AI tools and approaches, progress reviews throughout the project, and structured feedback at the final presentation.

What we’re building

An AI Transport & Timetable Assistant Chatbot for Andover College, sponsored by AiGentic Lab.

The college wants parents and students to get quick, accurate answers to everyday questions about getting to and from college: the cost of college coaches, timetables, and similar routine enquiries. Your chatbot will draw on college-provided information, answer in plain English, and hand over to a human whenever it is unsure.

You’ll start from a starter website that Vasilij has pre-built. It is deliberately bare: a welcome page with the brief and your Week 1 tasks, plus a placeholder button marking where the AI assistant will go. The assistant is yours to configure in Phase 2 – configuration first, not coding first.

Pushing to the main branch builds and publishes the site automatically. There is no deploy button and no manual step, which also means a broken commit on main is a broken live site.

Your job as a team: gather requirements, design the conversation, build the knowledge base, test with real users, and hand it over.

The most important rule: the learning objectives count even if the chatbot isn’t finished. Progress, teamwork and engagement are what matter.

Deliverables

1. Conversation design – question set, intents and example answers
2. Functional chatbot answering transport and timetable questions, with human handover
3. Test summary – accuracy and usability results with a feedback report
4. Technical documentation – README, setup notes, data sources, APIs used
5. Demo presentation with recommendations and next steps, plus a handover pack

How we work

Roles:

• Vasilij (AiGentic Lab) – technical lead / principal consultant and project sponsor
• You – junior consultants in a simulated software/AI developer role, working in small groups (2-3 students) that re-form at the start of each phase, each group owning a feature or component of that phase
• College staff – the customer. They provide the transport and timetable information, answer questions and receive your final presentation.

Rhythm:

• Project day is Friday, 09:00-16:30 at Andover campus, with limited remote working for coding and minor tweaks
• Work runs in informal weekly sprints: discover, build, refine
• Formal check-ins with feedback at the end of Weeks 1, 4, 9 and 12
• Each week has an interim goal – check the Schedule & Milestones calendar
• Update your tasks on the Task Board as you go. Move cards, don’t let them sit.

The three phases

1. Phase 1 – Research & Design (Weeks 1-4, 11 Sep – 2 Oct): kick-off, requirements from parents/students/staff, research existing FAQ chatbots, design conversation flows and the knowledge base
2. Phase 2 – Build & Test (Weeks 5-9, 9 Oct – 13 Nov): build the chatbot, connect the transport and timetable information, test accuracy and usability, fix issues
3. Phase 3 – Refine, Finalise & Present (Weeks 10-13, 20 Nov – 11 Dec): refine from feedback, produce the handover pack, final demonstration and exit review on Friday 11 December