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Activities & events
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#328 The Challenges of Enterprise Agentic AI with Manasi Vartak, Chief AI Architect at Cloudera
2025-10-27 · 10:00
Manasi Vartak
– Chief AI Architect and VP of Product Management (AI Platform)
@ Cloudera
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Richie
– host
@ DataCamp
The promise of AI in enterprise settings is enormous, but so are the privacy and security challenges. How do you harness AI's capabilities while keeping sensitive data protected within your organization's boundaries? Private AI—using your own models, data, and infrastructure—offers a solution, but implementation isn't straightforward. What governance frameworks need to be in place? How do you evaluate non-deterministic AI systems? When should you build in-house versus leveraging cloud services? As data and software teams evolve in this new landscape, understanding the technical requirements and workflow changes is essential for organizations looking to maintain control over their AI destiny. Manasi Vartak is Chief AI Architect and VP of Product Management (AI Platform) at Cloudera. She is a product and AI leader with more than a decade of experience at the intersection of AI infrastructure, enterprise software, and go-to-market strategy. At Cloudera, she leads product and engineering teams building low-code and high-code generative AI platforms, driving the company’s enterprise AI strategy and enabling trusted AI adoption across global organizations. Before joining Cloudera through its acquisition of Verta, Manasi was the founder and CEO of Verta, where she transformed her MIT research into enterprise-ready ML infrastructure. She scaled the company to multi-million ARR, serving Fortune 500 clients in finance, insurance, and capital markets, and led the launch of enterprise MLOps and GenAI products used in mission-critical workloads. Manasi earned her PhD in Computer Science from MIT, where she pioneered model management systems such as ModelDB — foundational work that influenced the development of tools like MLflow. Earlier in her career, she held research and engineering roles at Twitter, Facebook, Google, and Microsoft. In the episode, Richie and Manasi explore AI's role in financial services, the challenges of AI adoption in enterprises, the importance of data governance, the evolving skills needed for AI development, the future of AI agents, and much more. Links Mentioned in the Show: ClouderaCloudera Evolve ConferenceCloudera Agent StudioConnect with ManasiCourse: Introduction to AI AgentsRelated Episode: RAG 2.0 and The New Era of RAG Agents with Douwe Kiela, CEO at Contextual AI & Adjunct Professor at Stanford UniversityRewatch RADAR AI New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business |
DataFramed |
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Autonomous Data Products for the Autonomous Era: Rethinking Data Architecture for GenAI
2025-09-25 · 16:00
Zhamak Dehghani
– Founder and CEO
@ Nextdata
As enterprises scale their deployment of Generative AI (Gen AI), a central constraint has come into focus: the primary limitation is no longer model capability, but data infrastructure. Existing platforms, optimized for human interpretation and batch-oriented analytics, are misaligned with the operational realities of autonomous agents that consume, reason over, and act upon data continuously at machine scale. In this talk, Zhamak Dehghani — originator of the Data Mesh and a leading advocate for decentralized data architectures — presents a framework for data infrastructure designed explicitly for the AI-native era. She identifies the foundational capabilities required by Gen AI applications: embedded semantics, runtime computational policy enforcement, agent-centric, context-driven discovery. The session contrasts the architectural demands of AI with the limitations of today’s fragmented, pipeline-driven systems—systems that rely heavily on human intervention and customized orchestration. Dehghani introduces autonomous data products as the next evolution: self-contained, self-governing services that continuously sense and respond to their environment. She offers an architectural deep dive and showcases their power with real-world use cases. Attendees will learn the architecture of “Data 3.0”, and how to both use GenAI to transform to this new architecture, and how this new architecture serves GenAI agents at scale. |
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Autonomous Data Products for the Autonomous Era: Rethinking Data Architecture for GenAI
2025-09-25 · 12:00
Zhamak Dehghani
– Founder and CEO
@ Nextdata
As enterprises scale their deployment of Generative AI (Gen AI), a central constraint has come into focus: the primary limitation is no longer model capability, but data infrastructure. Existing platforms, optimized for human interpretation and batch-oriented analytics, are misaligned with the operational realities of autonomous agents that consume, reason over, and act upon data continuously at machine scale. In this talk, Zhamak Dehghani — originator of the Data Mesh and a leading advocate for decentralized data architectures — presents a framework for data infrastructure designed explicitly for the AI-native era. She identifies the foundational capabilities required by Gen AI applications: embedded semantics, runtime computational policy enforcement, agent-centric, context-driven discovery. The session contrasts the architectural demands of AI with the limitations of today’s fragmented, pipeline-driven systems—systems that rely heavily on human intervention and customized orchestration. Dehghani introduces autonomous data products as the next evolution: self-contained, self-governing services that continuously sense and respond to their environment. She offers an architectural deep dive and showcases their power with real-world use cases. Attendees will learn the architecture of “Data 3.0”, and how to both use GenAI to transform to this new architecture, and how this new architecture serves GenAI agents at scale. |
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IBM: Governing and Securing a New Era of Agentic AI with watsonx
2025-06-02 · 06:15
Geeta Gurnani
@ IBM India Private Limited
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Ratheesh Muraleedharan
@ IBM
The rapid advances in generative AI are fueling great excitement. Within just a few years, one-third of generative AI interactions are expected to utilize autonomous agents, propelling a new wave of productivity for enterprises. However, this potential can only be realized if the challenges surrounding AI trustworthiness, inferencing costs, domain-specificity, and effective and secure leveraging of quality enterprise data can be overcome. Data and AI leaders require a practical approach to accelerate AI adoption. Discover actionable techniques to maximize the value of your data for AI, learn from real-world examples of data and AI driven innovation in defence and aerospace, and gain insights into fostering greater AI productivity across your teams with IBM watsonx. |
gartner-data-analytics-india-2025
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Industry Leaders
2025-04-17 · 16:00
Which sectors are adopting AI agents and why. |
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AI Agents in Enterprise Operations
2025-04-17 · 16:00
How AI is streamlining tasks and enhancing decision-making. |
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Workforce Preparation
2025-04-17 · 16:00
Preparing your team for an AI-driven future. |
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Overcoming Challenges
2025-04-17 · 16:00
How to scale AI agents in your organization. |
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Generative AI in Enterprises: The Era of AI Agents
2025-04-17 · 16:00
Discover how AI agents are transforming enterprises, streamlining operations, and driving innovation. 📅 Date: Thursday, Apr 17, 2025 ⏰ Time: 12 PM – 1 PM EST (60 minutes) 📍 Location: Online 🔗 Register Now - https://cutt.ly/HrrnAGbO Why Attend? Generative AI is reshaping industries and operations. This webinar will show you how AI agents are driving innovation, improving efficiency, and giving organizations a competitive edge. What’s on the Agenda?
Hosted by Experts Get practical insights from industry leaders—no fluff, just actionable takeaways. 📢 Secure your spot today and lead the AI revolution in enterprises! |
Generative AI in Enterprises: The Era of AI Agents
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