SESAMm, a leading provider of AI-powered ESG and reputational risk data, is pleased to announce that Flexstone Partners, a global private equity investment manager and advisor, has selected SESAMm’s platform to strengthen its pre-investment screening and portfolio monitoring processes.

With approximately €10 billion in assets under management, Flexstone Partners invests globally across all private asset classes, including private equity, mezzanine, and infrastructure, through primary and secondary investments in funds, as well as direct co-investments in buyout & growth capital transactions. As a signatory of the UN-supported Principles for Responsible Investment (UN PRI) and an affiliate of Natixis Investment Managers, the firm integrates ESG considerations across its strategies and throughout the investment lifecycle.

As part of its investment process, Flexstone Partners systematically screens potential and existing holdings for controversies and reputational risks. The firm will now leverage SESAMm’s AI-powered ESG and reputational risk data to identify issues such as human rights violations, corruption, and environmental breaches, even among non-listed firms.

“This collaboration marks another milestone in our work with Natixis Investment Managers’ affiliates,” said Sylvain Forté, CEO and co-founder of SESAMm. “Flexstone stands out for its rigorous and forward-looking approach to ESG integration. We’re proud to support their teams with AI-powered insights that help strengthen due diligence and portfolio monitoring across their global investments.”

With SESAMm, users gain real-time visibility into ESG and reputational risks across millions of public and private companies worldwide. The platform leverages multilingual large language models to analyze content from over 4 million sources in 100+ languages, providing fully auditable data and early detection of potential red flags, empowering investment teams to strengthen both due diligence and ongoing portfolio monitoring.

“SESAMm’s controversy insights demonstrated both speed and quality, and the platform appears to integrate smoothly into our existing due diligence and monitoring processes. While we have not yet fully deployed the tool, we see strong potential for enhancing ESG risk identification and mitigation,” said Samira Boussem, Managing Director, Global Head of Sustainability Investment at Flexstone Partners. “We expect that it will bring a new level of efficiency to our analysis.”

About Flexstone Partners

Flexstone Partners ("Flexstone") 6 is an affiliate of Natixis Investment Managers, one of the largest asset managers in the world with over $1,427 billion in assets under management. The company manages $10.6 billion in assets 7and offers institutional investors worldwide tailored investment and advisory services in private equity. Flexstone's strategies in co-investment and the secondary market primarily focus on small and mid-cap segments, growth equity, and emerging managers in the United States, Europe, and Asia. With over 56 experts based in New York, Paris, Geneva, and Singapore, Flexstone’s international team addresses the needs of its clients around the globe. Composed of a team of specialists with complementary profiles, Flexstone has in-depth market knowledge and unique expertise in private equity. It is present in the most promising markets across North America, Europe, and Asia. For more information: www.flexstonepartners.com

About SESAMm

SESAMm is a global leader in controversy data, leveraging advanced large language models and generative AI to uncover ESG, reputational, and supplier risks in seconds. Our AI-powered platform surfaces real-time insights, even in low-disclosure markets, on millions of companies and infrastructure projects, supporting more informed decisions, enhanced due diligence, and regulatory alignment at scale. We work with leading firms, including Carlyle, Warburg, Natixis, RBI, Sustainable Fitch, Oddo, and others. SESAMm has raised $50M from renowned investors and operates across four continents. Learn more at www.sesamm.com

SESAMm’s AI Technology Reveals ESG Insights

Discover unparalleled insights into ESG controversies, risks, and opportunities across industries. Learn more about how SESAMm can help you analyze millions of private and public companies using AI-powered text analysis tools.

PARIS, December 16, 2021

SESAMm, an alternative data specialist at the forefront of AI-based text analytics, and EthiFinance, a non-financial analysis and consulting agency with expertise in sustainable development, are now working together to launch a new unique service: Identifying and scoring ESG controversies on European Small & Midsize Enterprises (SMEs).

When dealing with SMEs, a common issue with traditional data providers and rating agencies is the lack of coverage. Information gaps and opacity about a company can negatively affect asset managers in their investment decisions.

EthiFinance possesses strong expertise in rating SMEs – both listed and private – for the purpose of portfolio due diligence and monitoring. SESAMm’s TextReveal® tool leverages Natural Language Processing (NLP) to analyze more than 16 billion online articles and messages to track ESG topics.

“We have been working with SESAMm for months and have now reached a stage where we can deliver quality and depth of results needed to create reliable and relevant ESG alerts.”, shares Xavier Leroy, Head of Investor Services from EthiFinance  “Our teams of ESG analysts have enhanced and refined these alerts for controversies into our methodology, thus ensuring value to our clients”.

Controversy detections are notoriously difficult to assess and evaluate properly, be it the language barrier, lack of data, or difficulty for machines to work with ambiguity. The democratization of artificial intelligence and data science, the exponential growth of data, and wider access to more computing power have provided a fertile ground for new solutions to address this issue.

“Natural Language Processing is a game-changer, especially when working on ESG. Combined with alternative data, it helps us crunch billions of articles in dozens of languages and detect controversies very quickly” explains Sylvain Forté, CEO of SESAMm. “By fine-tuning TextReveal® with EthiFinance’s expertise in ESG, we are able to reach excellent results with 100% accuracy on the detection of critical controversies.”

SESAMm’s data and tools are leveraged globally by asset managers like The Carlyle Group, to conduct ESG studies for the purpose of due diligence, company analysis, and risk management. The partnership with EthiFinance breaks new ground thanks to its unique expertise in sustainability, ESG know-how, and very specific focus on European midsized companies.

SESAMm and EthiFinance have also developed a specific virality indicator to help assess how ESG controversies are spreading on the web. “This technological edge relies on an enormous amount of data which we can access through SESAMm’s platform,” shares Leroy.

A worldwide scandal, significantly impacting a company’s market price and its ESG scoring, can start from just one article or post, sometimes in a very niche community. SESAMm’s data lake, with its billions of articles and documents, serves as a real-time curated proxy of the internet enabling the timely detection of such scandals and the subsequent insights.

“This level of speed and depth of information not only represents a headstart when it comes to the competition but also a safety-net for asset managers, looking to monitor and manage their portfolio” confides Forté. “This innovative approach can be applied to other regions, Europe is only a starting point.”

The two companies are now working together to expand this innovative approach to listed companies across Europe.

About EthiFinance

Founded in 2004, EthiFinance is a non-financial analysis and consulting agency that supports its clients in managing risks and opportunities related to sustainable development.

EthiFinance develops services tailor-made to meet the specific needs of its clients, including investors, banks, companies and not-for-profit organizations.

Since 2017, EthiFinance has been working closely with Spread Research, a French financial rating agency (registered with ESMA) and independent credit research provider. The two companies are now part of the Qivalio Group.

Qivalio is an innovative European group providing rating, research, and consulting services in the field of sustainable finance. The Group provides solutions for investors, companies and organizations to address the challenges raised by financing as well as social and environmental transformations.

For more information: www.ethifinance.com/en/

About SESAMm

SESAMm (www.sesamm.com) is an innovative company specializing in alternative data and artificial intelligence for investment. Its team builds analytics and indicators, such as Sentiment Analytics, ESG Indicators, and investment signals by analyzing billions of web articles and messages using natural language processing and machine learning. With its NLP platform TextReveal®, SESAMm addresses the entire value chain of alpha research. With 6 offices including Paris, New York, London, and Tokyo, SESAMm works with major hedge funds, banks, private equity firms, corporate and asset management clients around the world for fundamental or quantitative investment use cases, market analysis and competitive insights.

For more information: www.sesamm.com

EthiFinance
23 Rue de Liège, 75008 Paris
margot.cazeaux@ethifinance.com

SESAMm
Malik Senouci
Head of Marketing and Communications
press@sesamm.com

The AI field is growing, and whether good or bad, people are doing more than talking about it; they’re using it more than ever. However, despite this increased use, I’ve noticed that, for some, their perception tends to alternate between false and too-high expectations of AI.

One case, in particular, was in 2021, Gartner placed natural language processing (NLP) at the top of its list of loaded expectations in terms of the Gartner hype cycle. As a result, many expected a potential “winter of AI,” so to speak. Yet, in 2022, we discovered the potential that we haven’t even touched on the true value AI could deliver.

Will there be a “winter of AI,” and are expectations bloated?

No, I don’t think so. As the past year has shown us, AI still has more to offer, a pocket of value that we have yet to see. I believe that while many people now accept that AI will be a transformative force—thanks to the fast democratization of large language models—our society hasn’t yet fully considered the actual changes it will make by lowering the barrier to access intelligence globally.

Progress in image generation, analysis, and computer vision—think autonomous driving—has leaped and bounded in the past year, and so has the progress in NLP, particularly in the natural language understanding (NLU) and natural language generation (NLG) aspects. We’re at a tipping point that will likely transform our world in the same way that the internet has.

Tipping point for AI

Today, we’re seeing the development of natural language processing through large language models, such as with the emergence of ChatGPT based on OpenAI’s large language model version GPT-3.

Astounding fact: ChatGPT’s growth in user adoption skyrocketed past one million users within a week of launching. In comparison, no other tech company has reached this feat in this short of a time frame. But the adoption rate is only part of it.

This advance has profoundly affected creative jobs because this might be the first time an AI generative system can create high-quality content. In public mode, users have tapped ChatGPT to do everything, from generating basic reports and ideas to writing lectures and producing code.

With a high adoption rate comes great opportunity. Any startup seeing this level of success could become the most funded project ever. And more, there’s revenue. OpenAI, as the example, could make one billion dollars by 2024, according to a report via Reuters.

On the other side of the same coin, however, there are greater risks due to AI generative system advancement. For example, with AI assistance, human hackers can develop more sophisticated phishing campaigns—hacking mechanisms based on social engineering.

Competition, specificity, and focus for AI advancement

Despite the risks, we still haven’t seen what’s yet to come with generative AI. GPT-4, for instance, is rumored to launch in 2023. I believe it will be a massive improvement over GPT-3, which is already mind-blowing.

And on the point of NLG and these large language models, there’s a lot that’s feasible in process automation. For context, creative content gets the most attention; it’s the area that makes more headlines. But I would also watch advancements in technical content and automated code generation, for example.

Process automation

Because of today’s AI advancements, it’s now possible for tools like ChatGPT to generate near-ready-to-use source code. That means instead of only being fun to play around with, these are becoming enterprise tools, making it possible for developers to automate technical tasks at scale.

NLP—specifically natural language understanding, which SESAMm works on—is not untouched by these applications. Many of these large language models can perform zero-short learning, which means NLU can be performed without pre-training, a huge advance in this industry. However, zero-short learning is insufficient for many advanced sentiment and ESG analysis tasks. We still need additional data sets to fine-tune the data for a specific purpose.

What does this mean for the natural language generation sector? Many startups—especially anything around chatbots—have folded, some just in Q4 of 2022. ChatGPT’s success means it’s solved and replaced the need for many of them, and basically, anything content creation on the B2C side has and will struggle.

Defensive edge

Otherwise, things are looking good in our sector. For example, at SESAMm, we’re focused on what I call “last-mile AI.” In our specific business application, you can’t bypass the need for a data set because we’re trying to attain a precise result for specific, often risk-related applications. Open-source large language models like GPT-3 and BERT can get you mostly there, and that’s fine for general purposes. But for “last-mile AI” applications, there’s a lot you can’t do without additional work.

And here lies what I think is one of SESAMm’s defensive edges: the “last-mile AI.”

Instead of finding ways to protect its algorithms, the AI business community would do better to defend its use cases because the algorithm’s value will decrease progressively. In contrast, the value of a use case’s purpose and the data set used to achieve the use case will grow.

Competitive edge

Computing power and the resources it takes to train large language models remain challenging to applications like OpenAI. It takes electricity, heat, and money to train these models, and AI has an environmental impact. So far, we’ve justified this cost in the name of optimization—meaning that we put in this extra cost upfront so that the likely efficiency will offset or reduce that cost later—but it’s still a cost to incur.

AI companies, especially those in the NLG space, will do well to find their competitive edges, areas optimized for a specific purpose like “last-mile AI.” Companies like OpenAI will likely continue to optimize their models for quicker responses but don’t necessarily have the problem of solving for a specific use case.

At SESAMm, for instance, a big challenge and expertise we developed in-house is inference time—or how quickly we can apply the model to an article or an individual sentence. Because we’re processing so much live content, the more time it takes to process—milliseconds multiplied by a billion—the more costly it is.

Our data lake currently holds over 20 billion articles, messages, etc., from over 14 years, and we add 10 million more daily. That’s a lot of content to analyze. But we make it so our clients can access the data within seconds.

The need to optimize models for fast inference and adapt to deep industry-specific use cases will remain one of the key reasons companies will have to continue re-training their own models. That doesn’t mean large language models don’t add value here. Their open-source versions simply become an impressive building block for any NLP application and accelerate the rate of innovation and productivity in the whole field.

My summary thoughts on AI for 2023

When Google launched BERT in November 2018, we quipped that Google had open-sourced this system as a joke because no one could put it into production because BERT was so big. Many companies didn’t have the computing capabilities to do anything with it at the time. Now we do.

This year, Google did it again; they released a model that’s even bigger than GPT-3. Of course, almost no one besides Google can put that model into production now. But my point is that there will always be computing, resources, and other challenges to making AI advancements. That’s why I think AI companies must focus on defensive and competitive edges.

Regardless of the challenges, I see good things happening in the NLU space being massively improved by large language models. I see improvements as we incorporate these models today compared to deep-learning models trained from scratch a few years ago. I also see a significant decrease in the amount of data we need to fine-tune results, reaching and focusing on the final client use case more quickly.

From a natural language generation perspective, I believe large language models will transform the world. And I’m really excited about this era because this transformation supports my deepest purpose, leveraging AI to accelerate innovative decision-making. We do this by giving decision-makers access to technology that analyzes research content, news, and discussions. And if we increase the rate of innovation or the quality of decision-making by 10% globally, the impact could be huge for all industries: healthcare, finance, fashion, you name it. Industry leaders can make better ESG and SDG choices that will affect our world on a grander scale.

2023 will be an exciting time for AI, specifically for NLG and NLU. Of course, we’ll continue to see AI innovations. But more importantly, leaders will have better insights to make better decisions, creators will create more—and more complex—content, and overall, the applications will become more specific to solving the needs of particular use cases.

Here’s to the new era of AI in 2023. Cheers!

About SESAMm

SESAMm is a leading NLP technology company serving global investment firms, corporations, and investors, such as private equity firms, hedge funds, and other asset management firms. SESAMm provides datasets and NLP capabilities through TextReveal^® to generate alternative data for use cases, such as ESG and SDG, sentiment, private equity due diligence, corporate studies, and more. With access to SESAMm’s massive data lake, comprised of 20 billion articles and messages and growing, its clients can make better investment decisions.