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Clarity AI to Expand ML and GenAI Product Development on AWS

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Clarity AI has expanded its presence in the cloud to take advantage of new capabilities that will enable it to better develop artificial intelligence (AI) products and services.

The US-based sustainability tech company will increase its presence on AWS and harness more of its tools to develop and test applications that Clarity AI can then roll out to its financial and corporate clients. Among the products it is excited about is AWS’ SageMaker suite of tools, which will help the company further integrate machine learning (ML) models into its products.

“It used to be that AWS would simply host a server for you to run anything that you want on that server, butrecently it has been offering higher-level services for developing ML models and deploying AI features,” Clarity AI CTO Marsal Gavalda told ESG Insight. “SageMaker is a way for us to host models; we build the model and then AWS gives you all the infrastructure for scaling,” Gavalda added. “Basically, it makes life easier and more efficient for our data scientists and engineers.”

Wider Partnership

Clarity AI has been using AWS to host much of its AI-focused data, analytics, and software services, including applications that use generative AI (GenAI). These feed into clients’ own systems, giving them access to insights on more than 70,000 companies and 430,000 funds.

The company is among a growing band of ESG data and technology companies that have already seized the computing power of AI. Many have chosen to do so in the cloud, which offers the storage and computational capacity to work on enormous volumes of data. Other technology specialists that have made explicit use of AI in their ESG offerings include UK-based ESG disclosures firm EthicsAnswers and data management giant Snowflake.

Gavalda said Clarity AI uses AWS for a multitude of use cases, including GenAI to discover new insights from large data pools, and to manage data governance and security. The expansion of the company’s presence on AWS has gone hand-in-hand with the closer integration of its engineering and data science teams to bring greater expertise to its product developments.

“We have in place a foundational engineering team that supports both engineering and data science, and they’re the ones that are starting to interface more with AWS,” he said.

Datasets and Solutions

Clarity AI distributes its services via APIs and widgets fed directly into clients’ workflows as well as via a web app. Its clients are predominantly financial institutions including BlackRock, Aviva, ING and BNP Paribas.

Its datasets provide transparency into climate, impact, risk and regulatory compliance topics including exposure screens and sustainable development goals impact assessments. Meanwhile its analytics and software offer solutions for carbon footprint calculations, a variety of sustainability-linked risk assessments and biodiversity impact measurement.

In the cloud, Clarity AI has the capacity to test and develop its pipeline of future products and services. Among them is greater use of GenAI and ML.

“GenAI has the potential to transform every application, business and industry,” said Matt Garman, senior vice president of Sales, Marketing, and Global Services at AWS.

Gavalda said the company is also looking at developing new ways for its clients to receive its data and analytics tools, potentially through direct access to cloud-based solutions.

“There have been some clients who may potentially have a preference for running software in their private cloud,” he said. “We’re exploring some of that, and certainly using AWS is a way to make that easier. To some extent cloud allows us to be more flexible about how we provide our services.”

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