About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

TurinTech innovates with Artemis code optimisation

Subscribe to our newsletter

TurinTech, a London-based technology vendor, plans to revolutionise code optimisation with its GenAI Artemis solution. Artemis is based on a proprietary large language model (LLM) – although it can be used with other LLMs – that is trained to help financial firms optimise software code, speed up execution, reduce cloud costs and lower carbon emissions. To date, Artemis has been implemented by investment banks in the UK, France and US.

The company was set up in 2019 by co-founders who met at University College London while doing PhD research work. They went on to work in financial institutions, where they experienced problems of getting code into production at any speed, internal bottlenecks holding up developers, and the pain points of code reviews.

 “There had to be a better way of doing things and a way to resolve these problems,” says Leslie Kanthan, CEO and co-founder of TurinTech, noting that while financial institutions tend not to have code optimisation teams, Artemis code optimisation can help them improve code quality, make developers more efficient, and give firms spending vast amounts of money on cloud savings of about 10% by optimising code, a potentially huge saving.

As well as optimising code and reducing costs, Artemis plays well into financial institutions’ sustainability goals by running better code faster, descreasing compute usage and providing energy savings.

Artemis scans software code on-premises or in the cloud. It uses TurinTech’s LLM, which has been trained on millions of lines of code and informed by the team’s proprietary knowledge, although it can also be used with other LLMs, perhaps less effectively, and takes hardware into consideration to allow legacy systems to perform to the best of their ability.

Use cases of the solution include identifying weaknesses in code and providing recommendations for optimal changes that enhance performance, noting code that could be sped up or improved by modifying particular lines, and analysing code bases to predict their efficiency – all with a human in the loop but reducing resource requirements overall.

Kanthan concludes: “Everyone wants to use AI, but will it add value to the business? LLMs are just another form of data, so you need apps for use cases. TurinTech has an app for code optimisation and is, at the moment, leading the market.”

Subscribe to our newsletter

Related content


Recorded Webinar: The roles of cloud and managed services in optimising enterprise data management

Cloud and managed services go hand-in-hand when it comes to modern enterprise data management (EDM), but how can the best solutions for the business be selected and implemented to ensure optimal data management based on accurate, consistent, and high-quality data, and delivering improved efficiency, better decisions and competitive advantage? This webinar will answer these questions,...


Data Veteran Puts his Expertise to Use in Altruistic Venture

Hany Choueiri has spent the past decade-and-a-half enabling some of the largest financial institutions in the world to make the best use of their data. Now he is freely giving his expertise to helping smaller firms do the same for themselves. The creator of data quality and management systems for HSBC’s European operations and the...


Data Management Summit New York City

Now in its 14th year the Data Management Summit NYC brings together the North American data management community to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.


Fatca – Getting to Grips with the Challenge Ahead

The industry breathed a sigh of relief when the deadline for reporting under the US Foreign Account Tax Compliance Act (Fatca) was pushed back to July 1, 2014. But what’s starting to look like perhaps the most significant regulation of the next 12 months may start to impact our marketplace sooner than we think, especially...