Building new
AI-powered, autonomous engines for growth

Philippe De Ridder

Philippe De Ridder

Co-Founder and CEO

In order to win in an increasingly autonomous world, driven by advancements in AI, leaders need to actively explore and define how AI can redefine their industries, from automating processes to creating entirely new product categories and business models. The future of innovation lies in our ability to envision a world where AI’s potential is fully integrated into the fabric of organizational creativity and growth.

We see three critical areas to focus on in order to become a leader in the increasingly autonomous world:

Below we’ll dive into building new engines for innovation and growth.

Building new Autonomous Innovation engines

With a clear view of envisioning the future, the next focus point should be to build autonomous engines for always-on innovation and growth. 

Engines that are capable of autonomously generating, validating and launching new concepts, accelerating the innovation process from years to days.

We partner with companies to develop real-world functional engines that – starting with simple prototypes act as co-pilots for human users and building towards autonomous systems that transform product innovation, manufacturing, and go-to-market. The engines are tailored to specific products, services and industries.

The following is a conceptual framework for how these engines work. The development of autonomous innovation engines requires a holistic approach, integrating insights, concept generation, and simulation engines. 

Hover and click through the interactive framework below.

Generally, it begins with a Learn capability that collects various data types—social listening, emerging patterns, scientific breakthroughs, weather data, customer service analytics, sales figures, and other proprietary data. This information fuels the Generate capability, which generates new product and service ideas, trained on data that’s relevant for the product or service. For example, in consumer goods, the engine is tailored to align with brand identities, and market demands.

The outputs of Generate are then evaluated through a Simulate capability. Here, we test desirability using synthetic customer panels—LLMs are increasingly capable of representing diverse consumer audiences and demographics. We also assess the feasibility and viability of these concepts simultaneously. Next, the Build engine creates the first prototype, incorporating elements like generative coding—with technologies like Devin, the potential here is rapidly growing.

Finally, the Launch engine explores autonomous methods for product launches, identifying the best way to distribute and market the product – as well as using real-world testing to create Synthetic Launches – in small-scale sandboxes before scaling the launch.

Examples of Autonomous Innovation engines

We envision, build and roll out autonomous innovation engine for our clients, across industries.

Leading CPG company

Working with a leading CPG company on transforming Innovation and building towards an Autonomous Growth Engine

Major global fashion retailer

Working with a major global retailer to reimagine how clothing is made, bought and sold in an AI-native way 

From the autonomous innovation engines we’ve built with clients, the concepts that are being generated hold their ground against traditionally generated product concepts and score well in consumer testing. We have compared the outcomes of our engines to human-made designs with real consumers to find the results to be comparable in desirability.

We’ve been doing this work across industries from consumer goods to fashion and in the B2B and industrials space too. The agents and parts of the engines communicate with each other, and concepts, products and services get iterated based on the ongoing feedback loop.

The most successful engines integrate multiple functions, impacting the operating model around it. Curious to learn more? Reach out to us with a question!