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
- Tweets3.5K
- Following642
- Followers11K
- Likes1.3K
Pinned Tweet
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
An interesting customer use case from yesterday's event, check it out 👇
Multiplayer AI, from a customer's perspective. 💛
At Product Spotlight, Pedro from enmacc shared how his team is building with AgentSpot and thinking about bringing those agents to more people across the business.
🎥 If you missed out on this event, you can catch the full recap here: bit.ly/4yHTYaK
Everyone go follow @AgentSpotxAI if you haven't already to keep up with AgentSpot features, news, updates, and inspiration. 🚀
What if everyone on your team could get trusted answers from your @databricks data without SQL or a ticket?
We’ll be at the #DataAIWorldTour to show what that looks like live.
📍 Chicago: October 29
📍 New York City: November 19
Free to attend, registration required: bit.ly/4iCvE52
AI anxiety is not just coming from employees. It’s also coming from the leaders responsible for making it work.
@karkhanis joined @KathleenWalch on the @PMInstitute's AI Today Podcast on what closes the gap between AI ambition and AI execution: trust, outcome focus, and governance that accelerates.
bit.ly/47xWvJy
It takes a village (and a whole lot of teamwork 💜).
A little appreciation for some of the crew behind yesterday's AgentSpot Product Spotlight!
Huge thanks to everyone who helped make it happen, including the many faces not pictured here. 🙌
What if your teammates could join the same conversation you're having with your AI agent? 😲
At today's Product Spotlight, François Lopitaux talked about how @AgentSpotxAI brings people and agents together through shared conversations and the ability to build, share, and customize agents across teams.
See for yourself and try AgentSpot free: thoughtspot.com/agentspot
Building an AI agent is one thing. Making it useful across an entire business is another.
ThoughtSpot's François Lopitaux spoke with TechTarget about how AgentSpot brings shared context, collaboration, and governance to enterprise AI. 🤝
There's a lot more to enterprise AI than just building an agent. Read the full conversation 👇
bit.ly/4zR19OT
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…
