H2O.ai flows into predictive and generative AI with expanded portfolio and audience in mind
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.
The vendor emerged from stealth three years ago to offer a machine-learning model observability platform, so organizations could watch models in production to see when and why they were failing. Aporia has now expanded into GenAI, resulting in its new AI Guardrails platform for mitigating risk in large language models in real time.
Generative AI has reframed expectations of AI by creating new types of content and paving the way for fresh use cases. This raises many questions around assessing the future value of analytics platforms, some of which have sat at the forefront of AI for many years.
The company's GRACE software platform is designed to address enterprise AI governance by serving up an environment for model development, deployment, management and governance. While 2021.AI's GRACE is in a market full of investment potential, this segment is likely to get more crowded and competitive.
An early pioneer in specialist software to make AI models adhere to governance considerations, the vendor has focused its go-to-market strategy on insurance companies from the get-go. How is Monitaur tackling this vertical, and what progress is it making?
The company has offered no-code data science from the get-go, and recently rounded out its platform with a large language model-based chatbot, automated data preparation and MLOps features to assist with model operationalization, to make no-code data science easier for analysts and data-literate business individuals.
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