Inrate, a Swiss sustainability data and ESG ratings provider, and SESAMm, a global specialist in AI-driven ESG and reputational risk data, have announced a strategic partnership to enhance ESG ratings with real-time controversy insights. Inrate will integrate SESAMm’s large-scale controversy event data, sourced from more than 4 million global data points and covering millions of companies, into its controversies assessment, ESG analysis, and ratings framework.
The collaboration aims to strengthen Inrate’s science-based impact ratings, which assess companies on the sustainability impact of their business activities and documented ESG controversies, rather than relying solely on self-reported disclosures. SESAMm’s multilingual, AI-powered text analysis will enable faster detection and broader coverage of ESG-related events, improving the timeliness and completeness of controversy screening.
Both partners emphasize the objective and transparent nature of their approaches, positioning the enhanced ratings as a tool for investors seeking robust, impact-focused ESG analytics for due diligence, portfolio management, and reporting. With this partnership, financial institutions gain deeper visibility into real-time ESG risks and opportunities across public and private markets, supporting more informed sustainable investment decisions.
About SESAMm
SESAMm is an AI-powered analytics company that supports ESG professionals with large-scale, text-based insights on environmental, social and governance risks and opportunities. Its core platform, TextReveal, analyses over 25 billion documents from more than 4 million sources in over 100 languages to detect controversies, sentiment shifts and sustainability-related events for around 5 million public and private companies worldwide. By transforming unstructured data from news, social media, blogs and other online content into decision-ready indicators, SESAMm enables financial institutions and corporates to strengthen ESG due diligence, monitor portfolios in real time and meet emerging regulatory expectations. The company delivers its analytics through dashboards, alerts, APIs and system integrations, combining machine-learning models with human quality checks to provide transparent, explainable and timely insights for risk assessment and impact-oriented investment strategies.
