Krishna Roy is a senior research analyst in the 451 Research technology research group within S&P Global Market Intelligence. She leads the data science and analytics coverage areas for the Data, AI & Analytics channel. Prior to this, Krishna was a research analyst in the Data, AI & Analytics channel covering business intelligence and data management, including data integration and data warehousing. Krishna arrived at S&P Global Market Intelligence through its 2019 acquisition of 451 Research, where she was a senior research analyst. During her 20-year tenure with 451 Research, she was responsible for many coverage areas, including business applications and business intelligence. Prior to joining 451 Research, Krishna held several journalist roles in London, New York and San Francisco. Krishna’s recent areas of concentration include data-driven decision-making, AI governance and compliance, and generative AI’s role in data science and analytics. Krishna holds a Bachelor of Arts, First Class Honors Degree, in English literature and American studies from Brunel University, London.
Generative AI may be creating all the buzz, but predictive AI is still relevant since it plays a critical role in enterprise data-driven decision-making. In this report, we discuss how DataRobot is addressing both areas due to the heightened interest in GenAI, where it is now focusing on large language models.
AI governance is a growing corporate priority led by heightened regulation and the need to manage and mitigate risks from generative AI. Credo AI has shed light on planned investment areas to solidify its AI governance focus following a fresh funding infusion in July.
The company, under new leadership led by longtime vice chair and now CEO Barry Libert, has doubled down on monetization opportunities surrounding the free Anaconda Python open-source distribution it came to market with over a decade ago. We look at how this strategy is playing out in its business and product development terms.
Continued adoption to improve strategic decision-making by using the more sophisticated analytical insights available from data science platforms than those possible using an analytics platform is a longtime growth driver for this market. It is now being joined by capabilities to enable enterprise implementation of diverse types of AI in a governed manner.
As organizations move from experimenting with generative AI to utilizing it for business use cases, the challenges to enable cost-effective adoption, while ensuring large language models do not go rogue or breach compliance mandates, mount. Trustwise is seeking to address these issues for GenAI as well as other AI workloads with its Optimize:ai API.
The company spent the last six years building a business to enable organizations to analyze data stored in cloud data warehouses. Having raised another sizeable funding round in a challenging funding environment outside of GenAI startups, the software unicorn is focusing on sustained profitability.
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