Safe and Sound AI is your go-to podcast for staying ahead in predictive and generative AI development. From pre-production design and post-production monitoring to governance and compliance, we deliver bite-sized episodes packed with technical insights and best practices. Designed for data scientists, engineers, trust and safety teams, and business leaders, our focus is to help you deliver and scale AI innovations with safety, trust, and transparency in mind. Safe and Sound AI is brought to you by Fiddler AI.
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Contact path
Public web form
Booking probability
26%
Guest openness
Selective
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Signup to Generate a PitchSafe and Sound AI is your go-to podcast for staying ahead in predictive and generative AI development. From pre-production design and post-production monitoring to governance and compliance, we deliver bite-sized episodes packed with technical insights and best practices.
Safe and Sound AI is hosted by Fiddler AI. The show has published 7 episodes to date.
Recent episodes include "The Anatomy of Agentic Observability" (28 October 2025, 16 minutes), "Agentic Observability: The AI Architect's Essential Blueprint" (24 July 2025, 14 minutes), and "How to Identify ML Drift Before You Have a Problem" (31 May 2025, 9 minutes).
Safe and Sound AI publishes roughly every few months, with episodes averaging 12 minutes across 7 episodes.
Booking probability for Safe and Sound AI is 26%, and the host is rated Selective on guests. Safe and Sound AI requires a Pod Score of 80 or higher. Safe and Sound AI's contact route on record: public web form.
The strongest fits for Safe and Sound AI are IT Services & Software Development. Safe and Sound AI has a technology audience.
Fiddler AI hosts Safe and Sound AI, a technology podcast with 7 episodes published.
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Episode #7
<p>As AI evolves from single agents into complex, multi-agent systems, the challenge of monitoring and trusting these autonomous collaborators grows. Traditional monitoring tools fall short, unable to interpret the...
<p>In this episode of Safe and Sound AI, we dive into the challenge of moving AI agents from impressive demos to robust, production-ready systems. We break down the principles of Agentic Observability, explaining how...
<p>In this episode of Safe and Sound AI, we dive into the challenge of drift in machine learning models. We break down the key differences between concept and data drift (including feature and label drift), explaining...
<p>In this episode, we discuss the new integration between Fiddler Guardrails with NVIDIA Nemo Guardrails, pairing the industry's fastest guardrails with your secure environment. We explore the setup process, practical...
<p>In this episode, we explore how Fiddler Guardrails helps organizations keep large language models (LLMs) on track by moderating prompts and responses before they can cause damage. We break down its industry best...
<p>In this episode, we explore two key approaches for monitoring AI models: metrics and inference observation. We break down their trade-offs and provide real-world examples from various industries to illustrate the...
<p>In this episode, we discuss how to monitor the performance of Large Language Models (LLMs) in production environments. We explore common enterprise approaches to LLM deployment and evaluate the importance of...
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