PRODUCT PLAYBOOK

6 Rules for Embedded
Analytics in the
Agentic AI Era

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Embedded analytics used to mean dashboards. Products still following that feature-based philosophy now face lagging adoption and ever-increasing support requests.

This playbook outlines six rules that will help you turn your in-product analytics into a differentiated user experience.

You’ll take away:

  • Industry benchmarks, analyst insights, and real user examples

  • Best practices for infusing agentic experiences into your product

  • A clear path to improved business outcomes, for both you and your users

If embedded analytics is part of your product strategy this year, read this first.
1745329820-photo-plain-eshan-hoque

Ehsan Hoque
Director of Product Management

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1745596328-photo-plain-brian-reynolds

Brian Reynolds
Global Head of Embedded, Go To Market

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ThoughtSpot Agentic Analytics Platform

Analyst Studio

Data Mashups, Data Science,
Python Notebooks, Ad Hoc SQL Analysis

Semantic Model

Trusted & Secure Metrics Layer, Agent-ready
Metadata, Data Security

Data Management

Real time, Zero Copy or In-Memory,
Unified Metadata and Compliance

AI Agents

Spotter - Agentic AI Analyst,
Deep Research, Agent as a Service

AI-Augmented Dashboards

AI-first, Mobile-ready, Automated Insights,
Connected Where You Work

Smart Apps

Embedded Analytics for your customers, Insights to
Actions, APIs and SDKs, Workflow Automation

Smart Apps

Automated
Insights

Data Hub

AI Agents

AI Augmented
Dashboards

Smart Apps

 

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