Engineering a GenAI-Powered Code Optimisation Platform Using Agent Collaboration and Evolutionary Algorithms
According to Y Combinator, one-quarter of the startups in its latest 2025 batch relies on AI to generate 95% of their codebases. While fast, the code generated has been proven to contain a number of inefficiencies, impacting performance and scaleability. Founded in 2016 by visionary computer and data scientists at University College London, Turintech’s core platform aims to address these inefficiencies – refining, validating, and evolving code, to improve performance, security, and scalability.
DataSpartan’s AI engineers have worked closely with TurinTech since its inception, helping to research, design, build and deploy their code optimization platforms Artemis and EvoML. Built on the TurinTech GenAI Intelligence engine(™), these platforms leverage agent collaboration, genetic algorithms, machine learning, and LLMs to orchestrate intelligent optimization and validation processes. As a result, organisations can easily analyze, optimize, and validate codebases at scale, improving performance and efficiency, while reducing costs.
In March 2025, TurinTech launched its Artemis product at Nvidia’s GTC event and announced to the world that it has successfully raised a total of $20 million in funding so far. The Artemis platform has been adopted by multiple industry leaders including Intel, who are turning to Artemis to help tackle real-world engineering challenges: from improving cloud performance and reducing technical debt to preparing legacy and AI-generated code for production.
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