Systems | Development | Analytics | API | Testing

Stop AI Hallucinations at the Source | Simba Intelligence

AI isn't failing because the models are weak. It's failing because the data beneath them is broken. 88% of AI pilots never make it to production. 74% of companies haven't seen value from AI. The uncomfortable truth? These failures aren't about intelligence—they're about access, governance, and context.

Cloudera Open Data Lakehouse: Seamless Data Management and AI #Cloudera #AI #Tech #Shorts

Modern enterprises are currently overwhelmed by massive, fast-moving data in various formats that traditional legacy warehouses simply cannot manage. Cloudera addresses these complexities with its open data lakehouse powered by Apache Iceberg, providing a single, seamless, and optimized view of all your information.

From Chaos to Clarity: How Spotter Unifies Healthcare Data for Better Decisions

Most healthcare teams are making decisions from multiple different dashboards and systems that don't talk to each other, which means someone is manually stitching together the picture—one that's always slightly out of date by the time it's ready. Outdated or incomplete data can lead to fragmented patient care and experiences. And no health system wants that. Whether tracking enrollment targets or auditing claims denials, Spotter applies standardized clinical logic to your unified dataset so you can focus on what matters: the patient. Go from chaos to clarity.

Spotter for Financial Services | Full Demo - March Spotlight

In the high-stakes world of financial services, an incomplete answer is more than a typo—it’s a liability that leads to compliance breaches, eroded client trust, and missed fraud. While general BI tools often force analysts into the weeds of manual data reconciliation, Spotter for Financial Services was engineered specifically to handle the industry's unique complexities.

Spotter for Supply Chain | Full Demo - March Spotlight

Supply chain leaders are constantly balancing supply and demand in a world where volatility is the only constant. But tracking disruptions after they happen isn't enough—true agility requires seeing them coming. In this session, Ivan Seow, our Senior Director of Product Marketing, takes the wheel for a deep-dive demo of Spotter for Supply Chain. He demonstrates how to move beyond reactive analytics and into a world of proactive, industry-tailored foresight.

The New Requirements for Mission-Critical Storage in an AI-Driven Enterprise

Most enterprises have made the commitment to AI. They’ve approved the budgets, stood up the pilots, and named it a strategic priority. So why are 95% of them getting zero return on $30–40 billion in GenAI investment? According to MIT research cited in Hitachi Vantara’s 2025 State of Data Infrastructure Global Report — which surveyed more than 1,200 IT leaders across 15 markets — the failure isn’t the model. It’s the infrastructure underneath it.

What CTOs Need to Know About Modern AI Storage

As organizations scale their AI initiatives from experimentation into production, CTOs face a pivotal architectural challenge as storage emerges as one of the most common—and most expensive—constraints. While organizations continue to invest aggressively in GPU compute, studies consistently show that infrastructure inefficiencies outside the GPU account for the majority of wasted AI spend.

Discovery Agent is Here! - Quick Explainer

Discovery Agent brings automated anomaly detection directly into Qlik Cloud. It monitors the metrics you care about, identifies meaningful changes, and delivers contextual insights right where you work. Today it’s a monitoring capability inside Qlik Cloud. Over time, it becomes one of the agentic services supporting autonomous workflows across the platform.