Making #analytics accessible, impactful, and scalable through artificial intelligence. Try it for yourself https://xitter.cf/t.co/IhIZ0ZAYqO
Mountain View, CA
Joined September 2013
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Cardboard wings. Lawnmower engine. Way too much confidence.
Some things shouldn't be DIY projects. Like your AI analytics.
Don't DIY. Embed with ThoughtSpot.
Will he fly? Find out.
bit.ly/47RmZFK
(This video is AI generated 😉 )
#EmbeddedAnalytics
The next era of enterprise AI is here. 🚀
Introducing AgentSpot: Multiplayer AI that brings people and agents together to build, share, and scale AI-powered work across the business.
Read the announcement 👇
bit.ly/3WjEH2b
What could your team build with AgentSpot? Find out today. 💡
Join Product Spotlight at 8 a.m. PT / 10 a.m. CT / 4 p.m. BST for real demos and a live building lab.
Don’t miss your chance to register before we begin: bit.ly/4ix2unS
Hands-on lab, live demos, AND an agent you can walk away with... Why wouldn't you join us!?
See you tomorrow 🥳
Not saying the boss made us post this, but... 👀
Product Spotlight is TOMORROW.
You coming? 👇
bit.ly/3UfkE4e
Date night: the table collapsed. 🕯️
Many, many tokens later: collapsed again. 🍽️
Dave’s talent isn’t the problem. Patching the same build forever is. Same goes for AI analytics in your product.
Build what differentiates you. bit.ly/4zNmngt
(This video is AI generated 😉)
#EmbeddedAnalytics #DIYDave
Nearly an hour of revenue accounting work. Now done in minutes.
Built with @AgentSpotxAI, using an agent a teammate had already created.
That's the power of #MultiplayerAI.
See it in action at tomorrow's Product Spotlight 👇
bit.ly/4iaeSc2
Almost every AI conversation eventually turns into a model conversation.
Three episodes of #TheDataAndAIChief with @GrantThornton, @Ligentia, @SwireCC make a different case.
The model was almost never the subject. Trust was.
See takeaways from their conversations here: bit.ly/4yBMPbV
“Why did five engines answer my question differently?”
In our BIRD analysis (Spotter, our agentic analyst, vs four competing agentic analytics engines), every engine answered the same questions over the same source data. Yet no two engines saw the same data model.
See how Spotter approaches simple, moderate, and challenging questions here: bit.ly/4yYXUow
The next era of AI isn't about giving everyone their own chatbot.
It's about teams building, sharing, and reusing agents that work with their business context.
That's the vision behind @AgentSpotxAI and Multiplayer AI.
Read the manifesto 👇
bit.ly/4A5kmMX
What's the difference between helpful personalization and feeling watched?
Our “Trust, Tested” report shows that the line is clear: shoppers accept personalization when they knowingly provided the data. The moment retailers reach beyond that, it no longer feels helpful.
See the report here: bit.ly/3WlrtSB
ALT A chart titled "Top Trust Triggers" lists different factors affecting trust: "Tracking behavior across other apps" at 57.6%, "Pushing recommendations too frequently" at 56.7%, "Using real-time location" and "Predicting needs before interest is shown" both at 48.7%, and "Referencing sensitive or personal topics" at 48.7%. The bottom of the image features the ThoughtSpot logo.
Imagine having 8–10 customer calls on your calendar and NOT having to spend hours preparing for them. 👀
8–10 customer calls a day. That's a LOT of prep work. 🫠
So Sarvesh built an AgentSpot app that pulls customer insights from Slack and Salesforce together with talking points, saving him 1–2 hours a day. Now, every CSM on his team uses what he created for their own accounts.
Build something like this for your team at Product Spotlight this Thursday, Oct 22. Link in comments to register. 👇
"Context lives in people's heads because organizations don't have knowledge management," says @jessicatalisman, during Day 1 of our Semantic & Context Layer series.
See the full conversation on why context feels so hard to capture: bit.ly/4s9HWFf
The migration conversation stops before it starts for most teams because the assumed cost in time and effort is too high to justify.
That assumption is worth revisiting.
Learn more here: docs.thoughtspot.com/cloud/2…
Wait, why does this make us actually WANT to tackle our Friday to-do list? 😎
One of the coolest things we've seen built with AgentSpot from our People Ops lead, and not a single line of code required.
Give DIY Dave a weekend and he’ll build anything. 💪 This weekend: a pool, two feet from the house. 👀
Dave’s talent isn’t the problem. Building the wrong thing is.
The shovel is the easy part. The hard part is everything underneath. Same goes for AI analytics in your product.
Part 2: bit.ly/4s77YsH
This video is AI generated 😉
#EmbeddedAnalytics
Most AI analytics pilots fail in three places: trust, governance, and speed at scale.
Cindi Howson joins @Verisk’s Louis DiModugno at our next step on the @Snowflake World Tour in New York on October 15 at 11:15am to share how Verisk addressed all three.
Booth #327 between sessions.
“It used to take weeks for regulators the get the answers they were looking for. Now with Savi-R powered by ThoughtSpot it takes seconds.“ @Verisk Global Chief Data Officer takes the stage at @Snowflake Summit NYC
Your next AI workflow could be up and running on October 22. 👀
We're excited to welcome Pedro Mayoral Picazo from Enmacc to Product Spotlight, alongside leaders from ThoughtSpot.
Don't miss it. Register today → bit.ly/4jmKsWw
The first question every data leader asks about AI isn’t about capability. It’s about control.
Spotter Analysts are governed from the start, certified models, access that travels with the analyst, and full traceability on every output.
See how it works: bit.ly/4dzG2b5
Most "AI for Good" projects don't fail because of bad algorithms—they fail because of how we structure human oversight.
Adding "Human in the Loop" checkpoints often degrades into passive rubber-stamping, decision fatigue, and false security.
@benzevgreen from @UMich shares how leaders can flip the script on the latest episode of #TheDataAIChief with @BIScorecard. 🎧
bit.ly/3W8IvmO
If you can track a pizza order in real time, why can't your business users see inventory levels and stock data the same way?
That's the expectation gap B2B software is facing right now.
Hear Jane Smith, Mark Hill-Smith, and Kim Faura from @Gumtree discuss why every business user, not just data scientists, should be able to query the data directly: bit.ly/47fMhNK