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Case Study

Scaling Australia's Leonardo.Ai through rapid enterprise growth

Project Highlights

Graceful scaling

Enabling rapid enterprise growth of Australian AI with 1000+ new customers in under 12 months

Robust stability

Introducing rigorous automated testing, expanding testing coverage and delivering crucial system stability

Seamless collaboration

Supporting existing teams to rapidly scale frontend, backend, user subscriptions, payment integrations and self-service

Uplifting ways-of-working

Established best practice ways-of-working, as a model for wider organisation adoption

Graceful scaling

Enabling rapid enterprise growth of Australian AI with 1000+ new customers in under 12 months

Robust stability

Introducing rigorous automated testing, expanding testing coverage and delivering crucial system stability

Seamless collaboration

Supporting existing teams to rapidly scale frontend, backend, user subscriptions, payment integrations and self-service

Uplifting ways-of-working

Established best practice ways-of-working, as a model for wider organisation adoption

Leonardo.Ai is a generative AI platform, that generates art, images and video with unparalleled speed and style. With the vision to become an entire generative content production platform it looks to incorporate numerous forms of Generative AI. Leonardo.Ai lets users save, edit and build multiple assets in the same style so they can be reused. Users can also train and build their own models for image generation.

Leonard.Ai’s generative AI platform

Challenges

Leonardo.Ai’s user base grew rapidly from 7 million to 15 million users over five months, and as such needed support for rapid scaling in terms of team augmentation and process improvements.

Generated by Leonardo AI

Our Approach

No Moss started working with Leonardo.Ai in June 2023 to support their backend and API teams amidst this rapid user growth. We initially focused on enabling enterprise-level API usage, addressing thousands of concurrent requests by implementing a round-robin load balancing system.

Outcome

To ensure high confidence in system stability during broad changes, No Moss introduced rigorous automated testing protocols, expanding test coverage significantly. We also scaled the front-end, developing features for user subscriptions, payment integrations, and self-service options. We also established a “beacon” full-stack delivery team, adopting formal agile ways-of-working (Scrum). This team is being used as a model for rollout to other teams at Leonardo.Ai.


Result

Leonardo.Ai saw improved API scalability, backend stability, and substantial growth in enterprise user support. This new line of business has over 1000 enterprise customers in less than a year and helped it secure funding investment.

What we delivered

This product delivery engagement featured:

  • A large highly skilled development team with specialisation in AI
  • API launched in two months
  • 12 month duration
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