Enterprise AI Solutions Need to be Different - Glean and ex-Slack CPO, Tamar Yehoshua, on RAG, Changing Behavior and Bring-Your-Own-Model.
Sep 10, 2024
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Tamar Yehoshua, a seasoned tech leader with a notable history at Amazon, Google, and Slack, shares insights from her current role at Glean. The conversation dives into Glean's innovative AI platform designed for enterprise solutions. Tamar discusses the importance of security and privacy in AI, the evolution from traditional search to generative AI, and the unique challenges enterprises face in adopting AI tools. She envisions a future where AI assistants take over routine tasks, allowing teams to focus on creativity and strategic initiatives.
Glean's innovative retrieval-augmented generation architecture seamlessly combines search and generative AI to enhance enterprise information retrieval.
Prioritizing security and privacy, Glean ensures compliant data access while enabling user-friendly interactions with proprietary SaaS information.
Deep dives
Overview of Glean's Capabilities
Glean is an enterprise AI platform designed to enhance information retrieval across various SaaS applications like Microsoft Office 365, Google Workspace, Salesforce, and Slack. It allows users to ask questions in natural language about their proprietary data, akin to using ChatGPT but within the confines of enterprise information. Users can inquire about elements such as account executives or sales briefings, significantly streamlining their preparation for meetings without waiting on a Customer Success Manager. Additionally, Glean plays an integral role in building no-code applications, providing a user-friendly platform for creating customized AI-driven solutions.
Security and Privacy Considerations
Glean prioritizes security and privacy, ensuring that it comprehensively understands the permissions associated with various SaaS applications before facilitating searches. By leveraging over a hundred connectors, Glean respects the privacy policies of different applications and ensures that users only access information they are authorized to see. The platform proactively identifies sensitive documents and integrates AI governance modules, allowing organizations to set restrictions on what information can be accessed. This privacy-centric approach aims to mitigate risks associated with unauthorized access to confidential data within enterprise systems.
Integration of Generative AI in Search
Glean's architecture employs a retrieval-augmented generation (RAG) framework that integrates both search functionality and generative AI capabilities. This innovative design allows the platform to not only return relevant documents but also present synthesized answers based on context gathered from various sources. User engagement with Glean is enhanced through an intuitive interface that presents AI-generated responses alongside traditional search results. This dual interface facilitates a more comprehensive utilization of enterprise data, empowering users to seamlessly toggle between seeking specific documents and receiving broader insights.
Challenges and Future of AI in Enterprises
As enterprises become more receptive to implementing AI solutions, organizations face the challenge of managing user expectations and understanding the capabilities of generative AI. Many employees may struggle to grasp how to fully utilize AI tools, resembling the early days of search engine usage where query formulation was crucial. While enterprises are eager to adopt AI, change management strategies will be essential to help users integrate AI effectively into their workflows. Looking ahead, the aim is for AI tools to automate repetitive tasks, allowing employees to focus on higher-value activities and ultimately transform workplace productivity.
In this episode of AI Native Dev, host Guy Podjarny sits down with Tamar Yehoshua, a seasoned tech leader with an impressive career in engineering and product leadership roles at Amazon, Google, Slack, and currently, Glean. Tamar shares her journey and the innovative work being carried out at Glean, an enterprise AI platform. The discussion delves into Glean's dual interface for search and chat, the critical importance of security and privacy in AI solutions, and the architectural insights behind Glean's RAG-based solution. Tamar also sheds light on the evolution from AI to generative AI at Glean, the challenges of building AI solutions for enterprises, and strategies for user adoption and behavior change. Looking ahead, Tamar envisions a future where AI assistants handle repetitive tasks, allowing employees to focus on more creative and high-leverage activities. This episode is a must-listen for anyone interested in the future of AI in the enterprise.