Systems | Development | Analytics | API | Testing

Our own sales team was losing up to 2 hours per account just switching between tools. Here's how they got that time back. In this video, our SVP of Revenue Strategy walks through how her team built a single sales hub with AgentSpot, pulling data from ThoughtSpot, Salesforce, Gong, and external intent signals into one workflow. What you'll see: What's hot in your territory: the accounts showing real buying intent, based on search trends and ICP fit.

How does our sales and revenue operation teams use Spotter, our agentic analyst, to instantly access and analyze their data using natural language? In this video, you'll see how Spotter makes data interrogation easy and reliable. Learn how to: Explore Data Sets: Quickly understand what data you have access to, where it is pulling from, and get immediate examples of what you can ask. Get Instant Answers: Type a natural language question (like "What's the booked ACV this quarter by region?") and instantly receive easy-to-read charts and deep analyses.

As enterprise AI scales, traditional data architectures are reaching their limit. Workloads are becoming more distributed, data movement is accelerating, and tech leaders face growing pressure to justify AI spend while delivering real business impact. Chief Technology Officer Sergio Gago breaks down key findings from Cloudera’s latest global survey of enterprise architects, data architects, and cloud leaders.

Qlik's MCP server just got three new lookup tools built for data engineering. They connect directly to your Qlik Cloud tenant, so coding agents can pull the real project values a pipeline needs instead of working from an empty template, find spaces and data connections by name, and browse the tables and views available on a connection, just by asking in natural language. That means easier declarative pipeline creation, with real tenant context built right into your prompt for faster, more accurate iteration.

Meet Winny, a GTM Intelligence agent built with AgentSpot and ThoughtSpot. See how teams can get faster answers to questions about conversion and pipeline velocity by simply asking questions in AgentSpot or Slack, with verified data pulled directly from ThoughtSpot. What is AgentSpot? AgentSpot is multiplayer AI for your business. Anyone can build, share, and collaborate with AI agents connected to your company’s data, context, and tools.

Most companies are investing in AI. Very few are seeing it reflected in their financial results. The gap comes down to three foundational decisions. In this clip from The Data & AI Chief, Raman Tallamraju from Vanguard breaks down what the companies seeing measurable AI benefits have in common.

Most organizations are moving fast on AI ambition. Fewer are moving fast on what makes that ambition possible. Before you can reimagine your business with AI at its heart, your data estate needs six things: to be well-defined, trusted, well-connected, contextualized, consumed in a multimodal way, and ready for both humans and machines at scale. Most organizations have two or three. The ones pulling ahead in AI have all six.

Get a quick look at Declarative Pipelines in Qlik Talend Cloud in just 4 minutes. In this video, Mike Tarallo from Qlik shows how you can go from intent to a working data pipeline using a declarative, code-driven approach, leveraging Claude Code, VS Code and Qlik Talend Cloud to generate the YAML and supporting files needed to define your pipeline.

New hires always have questions, and waiting on a response slows people down on day one. In this video, we use AgentSpot to build an Employee Policy Helpdesk Agent that pulls from your internal knowledge base and policy pages to answer everyday HR questions accurately, without paraphrasing or guessing. It knows when to escalate to a human and deploys directly in Slack so employees get answers right where they already work.