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By Dushyant Bansal
Our CEO recently wrote reaffirming an architectural decision ThoughtSpot made when LLMs first emerged: we do not use LLMs to directly generate SQL. My team has spent the better part of a year building AgentQL: a capability that doubles down on our decision. So let me explain what we actually built, why it doesn't just honor that architectural decision but depends on it, and the engineering choices underneath.
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By Nicolas Rentz
The journey to AgentSpot didn't start with a traditional product roadmap or a speculative “what if” from our R&D labs. Instead, it was born out of a growing friction within our own walls and became a "frontier R&D project" fueled by engineers exploring the internal potential of generative AI. When we first launched SpotGPT, our internal genAI application (similar to ChatGPT, but trained on internal resources) we saw immediate and massive adoption.
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By Micheline Nijmeh
Your team already knows when a campaign starts to underperform, when spend spikes, or when web traffic shifts. What you don't have is the speed to turn that insight into action. Someone still has to investigate, decide what to do, pull in the right people, and coordinate the work. That takes time. As a data-driven CMO, I've lived this every day. I can know the instant something changes in the data, but there's still a large gap between insight and action. Today, we're closing that gap.
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By Francois Lopitaux
When the Open Semantic Interchange (OSI) initiative launched last year, it set out to solve a problem every data leader recognizes: the same business metric gets defined a dozen different ways across a company's BI tools, warehouses, and now, AI agents. "Monthly active users" in the CRM rarely matches "monthly active users" in the warehouse, and every new AI copilot added to the stack makes the gap more visible, not less. That initiative has just taken its most consequential step yet.
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By Jane Smith
A Head of Product at a major sportswear retailer has a brilliant idea: let’s build an app that sales staff on the shop floor can have on their tablets, and ask their questions there and then, where they serve customers. They set about building. In order for the app to answer questions, it needs to have the information from the 2026 Spring/Summer Catalogue, a mammoth manual, let’s say 300k tokens.
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By Ivan Seow
I'll be honest: one number from the latest embedded analytics research stopped the entire planning conversation for this webinar. 57% of teams with embedded analytics report no measurable business impact, and that means not low impact or underwhelming impact, but no measurable impact at all.
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By Jochen Olbrich
For years, the "Data-Driven" dream has looked a lot like a crowded screen. We built dashboards for every department, every KPI, and every niche project. But as we reached "peak dashboard," a frustrating reality set in: we were drowning in visualizations but starving for immediate insights.
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By Katie Marcham
What an incredible day at the Agentic Analytics Playbook EMEA event! It might have been baking hot outside, but inside the Nobu Hotel, the energy was absolutely electric.
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By Team ThoughtSpot
Monthly active user rates stuck at 23%. A Slack message about another client who can't find the data they need. A support ticket your team has started to joke about: “Can you export this to Excel?” Once upon a time, embedding dashboards inside your product was a differentiator. Today, this is what the feedback looks like when your analytics stop working. AI agents can now respond to complex questions with meaningful insights in seconds.
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By Anant Agarwal
You ask your agent a question. The answer is slightly off. You point out the gap. Spotter fixes it, and that fix doesn't disappear when the session ends. Your team doesn't re-explain the same thing tomorrow. The next analyst doesn't start from scratch. The correction stays, and the work gets better from here. That's what memory makes possible. Not just for you. For everyone who comes after.
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By ThoughtSpot
Customers and champions report problems in Slack, but if nobody files the ticket, the issue disappears before it ever reaches Jira. In this video, we use AgentSpot to build a Slack to Jira Coverage Workflow that reads your champions channel every morning, cross-compares it against your Jira backlog, and emails you a report of every issue raised in Slack that no one has filed yet. What is AgentSpot? AgentSpot is an Agentic Workforce Platform for building workflows that make decisions, take action, and deliver results across every system your business runs on, grounded in your data.
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By ThoughtSpot
Discover what’s possible with AgentSpot as Sheila showcases an AI agent ("Leasey") built to automate lease accounting. From analyzing contracts to creating calculations, schedules, and audit documentation, this workflow shows how teams can use agents to streamline everyday business processes. What is AgentSpot? AgentSpot is an Agentic Workforce Platform for building workflows that make decisions, take action, and deliver results across every system your business runs on, grounded in your data.
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By ThoughtSpot
Check out what’s new in ThoughtSpot’s latest release! Spotter User-Level Personalization: Spotter now builds memory from your individual conversations, remembering your personal preferences, so it adapts to how you work and you spend less time repeating yourself. SpotterViz for Embedded Liveboards: Embed SpotterViz directly into your embedded smart dashboards and empower your users to build, edit, and explore decision-ready dashboards in minutes.
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By ThoughtSpot
For most enterprises, autonomous AI agents still feel like a risk waiting to happen. Andi Gutmans, Vice President and General Manager for Data Cloud at Google, joins Cindi Howson to explain what it takes to build the data foundation that trustworthy agentic AI depends on. He breaks down how organizations can finally activate the 90 percent of enterprise data that's unstructured, why tokenmaxxing is the wrong way to measure AI value, and how open standards like Apache Iceberg are helping leaders tear down fragmented, multi-cloud data silos and unify data across clouds.
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By ThoughtSpot
Silicon Valley has been measuring AI success by token consumption. The more tokens, the more AI transformation. Right? Wrong. Andi Gutmans, Vice President and General Manager for Data Cloud at Google, joins Cindi Howson on the podcast to share that the best context is the context that drives the outcomes you need with the least amount of tokens and processing. Efficiency, not volume, is where the real value is.
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By ThoughtSpot
Stop saying "Data Governance." Start saying Data Enablement. If your team thinks governance is just red tape, you’re doing it wrong. True governance is a foundation of accountability that ensures high-quality data flows everywhere. Bring your team along on the journey. Show them that a little bit of process right now means they get to make decisions faster and better tomorrow. Trust the data. Speed up the business. Learn more from Swire Coca-Cola's Bharathi Rajan on podcast.
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By ThoughtSpot
The SaaS purge is here, and it’s survival of the fittest. On the latest, Joshua McKenzie (@elmosoftware) drops a harsh reality check: If your software isn’t the ultimate "system of record," your customers are already plotting to build over you. If you're just a pretty interface, you're replaceable.
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By ThoughtSpot
Managing a $3 BILLION supply chain comes down to just 3 simple questions... @swirecoca-colausa6473’s VP of Data, Bharathi Rajan, reveals why you need to ditch the complex frameworks and AI hype before you try to scale. ThoughtSpot’s Cindi Howson drops the ultimate truth bomb: Stop waiting for "perfect" infrastructure. Use what you have today to win. Tune in to for the full blueprint! Music: “The Clermont” by Flash Fluharty Licensed via PremiumBeat, ID: P9IHFMDYNZCKLEFZ.
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By ThoughtSpot
ThoughtSpot has been named a Leader in the 2026 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms. We’re celebrating this milestone while building for tomorrow, as we shift from the Era of Reporting into the Era of Action. Hear a message from our CEO Ketan Karkhanis on what this shift means for our customers and partners, and how companies can win in this next era of AI BI.
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By ThoughtSpot
Check out what’s new in ThoughtSpot’s latest release! SpotterModel gets smarter: Build complex data models with AI formula suggestions and instant version rollbacks if you make a mistake. No stress, no lost work. Spotter Instructions: Fully customize Spotter’s persona, formatting rules, and strict guardrails. It says exactly what you want it to say—and nothing it shouldn't. Ad Hoc Analysis: Drop local files directly into Spotter for instant answers, or blend them safely with your governed enterprise data.
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By ThoughtSpot
For more than 20 years, dashboards served as a foundational element of business intelligence, helping leaders visualize and share valuable data across their organization.
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By ThoughtSpot
Businesses today run on apps, and those apps run on data. Too often, however, the technical complexity required to surface and explore that data for additional analysis prevents users from doing so. With ThoughtSpot Everywhere, organizations are easily building new data apps powered by the simplicity and ease of use of ThoughtSpot, or adding ThoughtSpot services to their existing SaaS offerings. This is giving them the unprecedented opportunity to create product experiences that stick, monetize data in new ways, and harness data right within existing tools.
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By ThoughtSpot
We are living in an unprecedented time driven by rapidly changing economic scenarios, the rise of digital native organizations and growing digital revolution, and the emergence of transformative business models. At the heart of much of this revolution is data. Organizations are collecting, analyzing, and mining data at an accelerated rate, creating new opportunities for powerful insights that deliver significant business impact.
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By ThoughtSpot
Today, just 24% of organizations say they've succeeded at becoming data-driven.* This is a challenge many data leaders are still struggling to solve despite increasing demand for data-driven insights from business users. Migrating to a cloud data warehouse is a good first step-and many have done so-but introducing new technology is not the same as ensuring adoption. To truly reap the benefits of your cloud data warehouse investment, you need an equally fast, scalable, and easy-to-adopt analytics solution to make your cloud data available to all.
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By ThoughtSpot
Although making predictions about the future is difficult even under the best of circumstances, it's never been more important for business leaders to focus, prioritize, and act in order to stay ahead of the technological curve-and the competition. The strategies you used to innovate and grow your business in the past will not be the same ones you use today. Rethinking how you use data to react and proactively adapt to change will be critical to your bottom line.
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By ThoughtSpot
Despite huge investments in data and analytics over the last two decades, many companies are still struggling with how to become truly data-driven. What are data leaders doing at the organizations that have figured it out? In this white paper, DATAcated Academy's Kate Strachnyi explores four key strategies for critically evaluating your entire data and analytics stack and systematically removing the barriers that exist between their business users and business-critical insights.
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ThoughtSpot is the Modern Analytics Cloud company. With ThoughtSpot, you can put the full power of your modern data stack in the hands of every employee and customer with consumer-grade analytics.
Why Everyone Loves ThoughtSpot?
- Instant Insights for all: Stop waiting for custom reports from data experts and instantly answer ad-hoc data questions on the fly.
- Unleash the value of your cloud data: Maximize the value of your cloud data warehouse and accelerate speed-to-insight for everyone across your business.
- Build Interactive Data Apps: Drive adoption by embedding search and insight-driven actions into your apps using our low-code developer-friendly platform.
- Bye-bye backlog: Empower non-technical people to answer their own data questions, while you build a single source of truth with security and governance at scale.
Welcome to the Modern Analytics Cloud.