How AI changed performance engineering (2 years later)
We thought the lemon had no more juice. AI proved us wrong.
Bring Your Full Intercom History Into Your Stack Using Intercom Connector
Sync contacts, conversations, tickets, and eight other Intercom streams into your warehouse, CRM, or AI pipeline, fully transformed, on a schedule you control, with no engineering required. Intercom is where support and product teams live for customer conversations. It's the system of record for tickets, live chat threads, help center articles, and the segments and tags teams use to organize customers by plan, behavior, or lifecycle stage.
The 3 Things Companies With AI ROI Have in Common
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.
Centerprise AI: Add New Banking Systems Without Custom Integration Projects
Your next banking initiative shouldn't wait on another custom integration. Keep your core banking system and connect everything around it with Centerprise AI. Describe the pipeline you need, and it generates the connections, mappings, transformations, and data quality checks across APIs, databases, legacy systems, and more.
Automated Invoice Processing with ReportMiner
Automate invoice processing end-to-end, without worrying about changing invoice formats or manual errors.
Is Your Data Estate Actually Ready for AI? The 6 Characteristics That Matter
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.
From Chatbot to Compound AI System: Infrastructure Patterns for Multi-Model, Tool-Using Applications
Two years ago, GenAI in production usually meant a single LLM serving a single endpoint. In 2026, it usually means much more. The applications shipping in front of users today are compound AI systems: orchestrated pipelines of retrievers, embedders, dialogue models, classifiers, code interpreters, SQL executors, and tools, with a single user request fanning out to several model calls across the stack.
The evolving role of the CDO in the AI era
The CDO’s job can be boiled down to ensuring data access, building innovative data products, and managing data responsibly.
9 Low-Cost SaaS Metrics & KPI Dashboard Tools That Are Ridiculously Easy to Set Up
The best SaaS metrics dashboard software doesn’t have to cost enterprise money. Every tool on this list is priced for growing companies, sets up without a demo call, and pulls your key metrics out of the apps where they’re trapped. If you’re a SaaS company specifically, we’ve built a dedicated home for this problem: see how Databox works as the best SaaS metrics dashboard software for finance, product, and go-to-market data.
Declarative Pipelines in 4 minutes
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.