FutureSpark

The Challenge

FutureSpark set out to rethink tutoring for students in grades 7–12. Traditional options were costly, inconsistent, and hard to schedule, frustrating many families. The founders envisioned something smarter, accessible, and truly personalized.

The roadblocks were clear

High tutoring fees excluded many students who needed help.
Learning outcomes varied, with progress often uncertain.
Scheduling conflicts made consistent support nearly impossible.
Current tools lacked the mentorship and adaptability students expected.
Building subject-specific AI meant developing two different teaching logics.

The mission was ambitious

Create an AI-powered mentor that could deliver personalized learning at scale and help Canadian students gain confidence in their most challenging subjects.

The most complex challenge was combining two distinct approaches: Math, grounded in the KST methodology, and English, built on a hybrid model. Both needed to feel like a real mentor, guiding each student according to their learning style.

The Idea

FutureSpark’s vision was to go beyond simple homework support.

The founders wanted an AI mentor, a tool that would answer questions and guide students through challenges based on their unique learning styles.

The objectives were ambitious

An AI-driven mentor experience that adapts to how each student learns, turning Math and English into subjects they could confidently approach.

A user-friendly platform that motivated students while giving parents visibility into progress through clear reports.

Personalized learning plans generated from initial knowledge assessments, ensuring every student received targeted support.

Key features included

Parent-managed accounts

Parents create profiles and invite one or more students.

Seamless student onboarding

Students join via an invite link and complete a questionnaire to identify their learning style, visual, kinesthetic, or reading/writing.

Knowledge assessments

Personalized plans are built from initial subject evaluations.

Role-based dashboards

Parents and students each have tailored dashboards with unique views.

Subject-specific tracking

Students follow their progress separately in Math and English, with clear indicators of growth.

What makes FutureSpark stand out is its combination of AI mentorship, subject-specific teaching methods, and real-time progress tracking into a single platform designed for learners and their families.

The Solution

We developed FutureSpark as an AI-powered learning platform made to feel like a true mentor for students while giving parents clarity and control. The project followed a structured rollout, balancing educational complexity with scalable technology.

Step-by-step process

Proof of concept

Tested AI mentoring capabilities to validate feasibility.

Kickoff

Defined scope and mapped project priorities.

Requirements gathering

Outlined functional and non-functional needs for the MVP.

Design & prototyping

Created wireframes and student/parent-facing UI in Figma.

Core development

Built the multi-role platform in Bubble.io, with parent and student dashboards. Developed a temporary landing page to support early marketing efforts.

Integrations

Connected Stripe for subscriptions, Supabase and n8n for the AI mentor, and Progressier for mobile PWA.

Technologies Used

Bubble.io: Platform and website development.
Progressier: Progressive Web App for mobile access.
Supabase & n8n: AI-powered mentoring logic.
Stripe: Subscription management.

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Unique Approach

Dual methodologies: Math built on the KST model and English on a hybrid approach, reflecting subject-specific learning needs.
Role-based dashboards: Parents and students received tailored dashboards with personalized views of progress and results.

This process allowed FutureSpark to combine AI mentorship, tailored methodologies, and family engagement tools into one cohesive platform.