Systems | Development | Analytics | API | Testing

Direct to Lakehouse, No Detour: Announcing the Integrate.io Databricks Connector

Write pipeline output directly into Databricks tables, with staging and load handled automatically, so lakehouse teams skip the intermediate warehouse hop and get data where it belongs, without maintaining a manual copy step. Databricks has become the default lakehouse for teams that need one place to store, process, and query data at scale, from raw event logs to curated tables used for BI and machine learning.

How to Operationalize AI Pilots: Roche's Agentic Analytics

If there's one thing that stuck with me from Yannick Misteli's session at the Agentic Analytics Playbook event in London, it's this: most AI pilots don't stall because of technology or budget. They stall because nobody answered the "day after" questions. I had the opportunity to sit down with Yannick Mistelli, Head of Engineering at Roche, the global pharma company with 100,000+ employees and heavy regulation across 25+ countries.

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.

[AgentSpot Showcase Series] Winny - GTM Intelligence Agent

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.

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.

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.

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.