Systems | Development | Analytics | API | Testing

In the world of early-stage startups, the real enemies aren’t competitors. It’s time, focus, and credibility. You’re racing to ship fast, protect runway, and look enterprise-ready long before you actually are. And in 2025, every serious buyer expects your product to have native, AI-powered analytics built in. Not basic dashboards, but a polished, conversational, ask-anything, data experience that delivers trusted answers.

Your executives are asking for AI-powered customer experiences, but your data teams are still playing catch-up with basic self-service requests—and that gap is costing you competitive advantage every day it persists.

Snowflake Intelligence and ThoughtSpot are more than complementary tools—they complete the picture for AI-powered analytics and BI that serves everyone everywhere, from data scientists to business executives. Together, they turn data into decisions through one connected experience that works the way people do: intuitive, secure, and fast. No silos, no copies—just a single source of truth your entire business can trust.

For years, product teams from software companies have faced the same uphill battle: deliver analytics that hopefully fulfill their customers’ expectations while keeping their own roadmaps on track. Too often, the result is static dashboards tacked onto an application—uninspiring, difficult to maintain, and disconnected from user workflows. Meanwhile, customer expectations have evolved. They want analytics that feels alive, intelligent, and seamlessly part of the products they use every day.

With new AI capabilities, Spotter 3 blends structured and unstructured data, reasons like your best analyst, and turns every question into confident action.

At ThoughtSpot, we've long understood that a robust semantic layer is the linchpin of a successful data strategy. Our Agentic Analytics Platform is built on a semantic foundation that makes it possible for anyone to get trusted, instant answers from data using simple natural language. However, the industry has struggled with a foundational challenge for years: a lack of a common semantic standard.

As leaders across industries, we’ve all experienced the frustration of legacy BI tools—spending weeks building dashboards that end up unused, or struggling with rigid filters that block true exploration and insight. Calling this “data-driven” is no longer acceptable! Today, the pace of AI innovation has raised expectations. Customers and end users now demand instant, contextual, and explainable intelligence, seamlessly embedded into their daily workflows.

For today’s SaaS leaders, accelerating product roadmaps is a top priority. That’s why the most forward-thinking teams are embedding AI-native intelligence directly into the tools and workflows their users rely on every day. Recently, I had the privilege of speaking with product leaders from Tekion, Navan, and ASK BOSCO in ThoughtSpot’s executive masterclass on embedded analytics.

The strategy is strong, but the insight you need—clear, live, decisive—is missing. It’s buried in dashboards. Stuck in backlogs. Trapped inside tools that promised acceleration, but only slowed you down. We were told things would be different. That self-service would finally work. That AI would bring clarity. That decisions could move at the speed of business. But the promise fell short. You invested in business intelligence. What you got was a backlog.

AI is no longer a fringe experiment: it’s a mainstream mandate. But with that shift comes a new kind of pressure: to act quickly, to appear modern, to bolt on something “intelligent” before someone else does. For many teams, this leads to reactive choices. Features get prioritized because they sound impressive, not because they solve a real user problem. Familiar interfaces get copied instead of questioned.