Financial institutions are moving fast on GenAI, but not always forward. While the promise is clear (faster investigations, smarter automation, better service), scaling GenAI responsibly remains elusive. Banks face unique constraints: legacy infrastructure, fragmented AI stacks, rising model complexity, and a regulatory environment where oversight is not optional.| The Dataiku Blog
Enterprises already run mission-critical systems on AI, which makes governance non-negotiable. As Generative AI (GenAI) and AI agents scale into broad deployment, they bring new risks that directly affect customers and core business processes, including hallucinations presented as fact, biased or offensive outputs, and exposure of sensitive data to adversarial attack.| The Dataiku Blog
Ask any data analyst or scientist where their time goes, and the answer is consistent: half of it is lost to searching for data assets, redoing work, and manually documenting datasets, models, and insights. Unfortunately, this is still the dominant reality of data work in 2025. For years, organizations have treated this as background noise, an unavoidable cost of doing analytics at scale. But the waste has become too significant to overlook. When 50% of expert time is consumed by administrati...| The Dataiku Blog
Discover how modern Centers of Excellence can align with strategic priorities to deliver measurable business value and drive AI adoption in enterprises.| blog.dataiku.com
Every minute of unplanned downtime costs manufacturers thousands of dollars. Yet most teams are still flying blind when it comes to predictive maintenance.| The Dataiku Blog
Your customer data is scattered across multiple martech systems and point solutions. Your team spends most of their time manually preparing data instead of generating insights. Your IT department has a backlog for analytics requests that stretches for months.| The Dataiku Blog
Discover why we believe Dataiku is the AI platform of choice for enterprises around the world.| blog.dataiku.com
Learn how IT leaders can scale analytics and AI by balancing speed and control, modernizing infrastructure, and ensuring trust and governance.| blog.dataiku.com
Dataiku is recognized in the 2025 Gartner Critical Capabilities for Data Science & ML Platforms, Core Data Science report.| blog.dataiku.com
The blog discusses how CoE webinar highlights strategies for integrating governance into AI and self-service platforms, ensuring scalability and safety without hindering progress.| blog.dataiku.com
Discover the RAFT framework for responsible GenAI and how it can be applied to both traditional and GenAI systems.| blog.dataiku.com
Dataiku has expanded our ecosystem of LLM Mesh partners to address topics like model scanning, red teaming, data protection and privacy, and more.| blog.dataiku.com
Get an overview of where Dataiku fits in the NVIDIA Enterprise AI Factory, as well as a concrete example of building a visual agent in Dataiku.| blog.dataiku.com
Discover how to navigate the tariff storm with these three powerful tools against tariff turbulence, enabled by Dataiku.| blog.dataiku.com
What do the shockwaves of DeepSeek mean for organizations scaling AI in the enterprise? Find out here.| blog.dataiku.com
Discover four critical areas of AI risk (from GenAI to governance and more) and how Dataiku helps mitigate them across the entire AI lifecycle.| blog.dataiku.com
See how Dataiku, a 3x Gartner Magic Quadrant Leader, enables IT leaders to maintain tech optionality and agility with Dataiku.| blog.dataiku.com