hedgehog lab - teachmate - Empowering Teachers with AI-Driven Education Tools

hedgehog lab - teachmate - Empowering Teachers with AI-Driven Education Tools



The Lowdown
Teachmate is an AI-powered digital assistant transforming how teachers plan, deliver, and personalise learning. It saves educators over 10 hours a week with a growing suite of more than 150 tools, helping them create tailored resources with ease.
With over 370,000 teachers using Teachmate globally, the platform has become a trusted name in EdTech. Operating on a freemium model, it provides essential tools for free and offers advanced features through Pro licences for individuals, schools, and school groups.
As the user base expanded, Teachmate needed a more robust, scalable platform to support growth, improve reliability, and enable long-term innovation.

The Problem
Teachmate’s successful MVP, originally built on a low-code platform, began to show limitations as demand increased. The system struggled to maintain performance, integrate new capabilities, and support the rapid pace of feature development required in a competitive market.

Key challenges included:
Reliability and scalability: Difficulty supporting more than 370,000 users and maintaining reliable backups.
Development constraints: Limited ability to release new features or integrate with other platforms.
Admin flexibility: Restricted tools for managing and launching new offerings.
Revenue model limitations: Barriers to introducing enhanced features for premium and institutional customers.
Teachmate needed a complete rebuild to improve stability, empower internal teams, and unlock new opportunities for growth.

Our Approach
Using the Double Diamond methodology, we followed a structured process of discovery, definition, development, and delivery to ensure the new platform met Teachmate’s operational and strategic goals.

Discovery: Stakeholder workshops, user journey mapping, and technical audits uncovered the root causes of reliability and scalability issues.
Strategy: Business Model Canvas and Value Proposition Mapping aligned the product vision with commercial ambitions.
Delivery: Agile delivery cycles enabled continuous feedback and iteration, allowing the team to stabilise core systems and build new features incrementally.
This approach ensured a smooth transition from MVP to a resilient, future-ready platform.

The Solution
To overcome the limits of the legacy system, we rebuilt Teachmate from the ground up – transforming it into a cloud-native, scalable, and secure platform ready for global growth.

Key Technologies and Frameworks:
Frontend: React with TypeScript – enabling a fast, modular, and flexible user interface.
Backend: Python (Django) – delivering performance, reliability, and robust API connectivity.
Cloud Infrastructure: AWS (Lambda, RDS, S3) – providing autoscaling, resilience, and secure storage.
Authentication & Security: OAuth and role-based access control – ensuring data privacy and streamlined access management.
Analytics & Monitoring: AWS CloudWatch, Sentry IO, Google Analytics, and Amplitude – empowering real-time performance tracking and data-driven decision-making.
This modern stack gives Teachmate a future-ready foundation, capable of supporting advanced integrations, continuous growth, and the rapid development of new AI-driven educational tools.

The Product
The rebuilt platform significantly improves scalability, performance, and user experience. Teachers benefit from smoother workflows and faster access to tools, while administrators have greater control over content and new product offerings.
The new system not only resolves the limitations of the previous platform but positions Teachmate to expand into new markets and continue evolving their suite of intelligent teaching tools.

The Results
The platform rebuild has delivered transformative outcomes for Teachmate’s users and business:
Stronger performance and stability for more than 370,000 users
Higher user engagement observed during beta testing
Reduced operational overhead through improved admin workflows
Faster feature development thanks to a flexible, modular architecture
Greater potential for growth across new revenue models and markets
Teachers report smoother performance and more efficient workflows, giving them more time to focus on what matters most: teaching.

Read the case study here: Teachmate Platform Rebuild | EdTech Case Study by hedgehog lab