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Rajeev Shrivastava

CHIEF EXECUTIVE OFFICER

Rajeev brings extensive leadership experience from top technology companies. Previously, he drove significant growth and innovation at Google and NICE inContact, leading major strategic initiatives and successful mergers. His expertise in scaling businesses and fostering innovation is underpinned by an MBA from the Wharton School and a Bachelor’s degree from Delhi College of Engineering. Prior to joining TigerGraph, Rajeev was at Google, where he served as GM & Product Lead for an AI-first Customer Conversation Platform. In this role, he managed a significant P&L and led teams driving innovation and growth within Google’s expansive business landscape. Previously, Rajeev played a pivotal role in the growth of NICE inContact as their Chief Product & Strategy Officer. Prior to NICE inContact, Rajeev led go-to-market and marketplace initiatives at Rackspace.

A network diagram with connected icons representing people, devices, money, and shopping, illustrating data relationships. The TigerGraph logo is in the top left, with the text, Why Connections Matter More than Ever in Data Analytics at the bottom.
Why Connections Matter More Than Ever in Data Analytics
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An infographic comparing traditional machine learning, shown with isolated icons, to graph-based machine learning, shown with connected network nodes. Text reads: Think You Understand Machine Learning? Try It with Graphs. TigerGraph logo top left.
Think You Understand Machine Learning? Try it with Graphs
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A graphic showing interconnected nodes with the TigerGraph logo at the center. Three benefits—lower cost, faster answers, and higher accuracy—are listed, along with the title: The AI Factory Needs a Blueprint: Why TigerGraph is the Secret to Profitable Inference.
The AI Factory Needs a Blueprint: Why TigerGraph is the Secret to Profitable Inference
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Five people sit on a panel discussing how open banking compliance can be a competitive advantage, on a stage with a bright pink BANKING TRACK backdrop. A screen behind them displays the panel’s topic along with speakers’ names and photos.
From Compliance to Competitive Moat: Takeaways from Fintech Meetup 2026
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A flowchart by TigerGraph illustrating Why Payment Fraud is Now a Multi-Model Architecture Problem, showing steps: Sequence Learning, Relational Context, and Explainable Scoring, connected to icons and explanatory text.
Why Payment Fraud Is Now a Multi-Model Architecture Problem
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A graphic with icons representing a bank, email, and user profiles, connected by arrows and X marks. The title reads: Failed Update Patterns in KYC. How Identity Graphs Catch Trying to Become Someone Else. TigerGraph logo is in the corner.
Failed Update Patterns in KYC. How Identity Graphs Catch “Trying to Become Someone Else”
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A network diagram illustrating AML graph analytics for structuring and layering detection, with icons of banks, money, and stores connected by dotted lines. The TigerGraph logo and the title are shown at the bottom.
Money Laundering Detection with AML Graph Analytics’ Structuring and Layering 
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A diagram shows money transfer from Account A to Account B through a central bank icon, with two other banks below. Text: Capturing Cross-Border Routing Signals That Hide in Plain Sight. TigerGraph logo in the top left.
Capturing Cross-Border Routing Signals That Hide in Plain Sight
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