ThoughtSpot Sage is an AI-powered analytics tool that integrates GPT's natural language processing and generative AI with ThoughtSpot's patented search technology to facilitate more intuitive and accurate interactions with data. Users can engage with the system using plain English, enabling seamless querying and command execution. ThoughtSpot Sage aims to redefine the data analysis experience across various industries by providing a user-friendly interface for data exploration and insights generation.
ThoughtSpot Sage was launched on March 10, 2023. The key individuals involved in its creation are Sumeet Arora, who is the Chief Development Officer at ThoughtSpot, and Srikant Gokulnatha, the Senior Vice President of Engineering. ThoughtSpot itself was co-founded by Ajeet Singh and Amit Prakash, with the aim of revolutionizing the way data is analyzed and utilized for business decisions.
To use ThoughtSpot Sage effectively, follow these steps:
Connect Data Sources:
Model Data:
Interact and Analyze:
Visualize Data:
Monitor and Manage:
Secure Data:
Embed and Share:
Support and Accessibility:
These steps outline the core functionalities of ThoughtSpot Sage, including data connection, modeling, analysis, visualization, monitoring, security, embedding, sharing, and support. Utilizing these features will enable you to leverage the power of AI-driven analytics effectively.
Paid plans start at $1250/month and include:
I appreciate the intuitive natural language processing feature. It allows me to quickly ask questions about our data without needing deep technical knowledge.
The interface can be quite overwhelming at times, especially with the amount of data we handle. It feels cluttered, and I often find myself lost in the features.
ThoughtSpot helps me generate quick insights for our marketing campaigns, which allows me to make informed decisions faster. However, I find that the accuracy of the insights can vary.
The AI capabilities are impressive; I can type in questions in plain English, and it gives me relevant answers almost instantly.
Sometimes the system struggles with complex queries, which can be frustrating when I need detailed analysis.
It helps streamline our data analysis processes, reducing the time we spend on reports. This efficiency is crucial for our fast-paced environment.
The concept of using natural language for data queries is innovative and has potential.
Unfortunately, the execution is lacking. The tool is often slow and doesn't understand context well, leading to irrelevant results.
It helps in pulling data, but I often have to validate the results against other tools. This leads to more work rather than streamlining the process.