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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.

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Dark background with TigerGraph logo, scattered blue nodes converging into an orange circle, and text Context Defines the Decision. Source: McKinsey & Company, Rewired (2026).
Graph + AI
Tue 5 May 2026
McKinsey Is Right: AI Needs Context. Almost No One Has It.
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A digital graphic for TigerGraph features the text “Data isn’t the problem. Context is.” over a network graph with orange nodes forming an upward trend. Smaller text reads “Less noise. More signal.” TigerGraph’s logo appears in orange.
Graph + AI, Graph Databases
Fri 24 Apr 2026
Data Isn’t the Problem. Context Is.
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A graphic shows an AI stack with five layers: Applications, LLMs, Vector Databases, Relationship Runtime for AI (highlighted), and Data. Text reads, Your AI stack is missing a layer. Add the relationship layer. TigerGraph logo included.
Graph + AI, Graph Databases
Tue 21 Apr 2026
The Missing Layer in Your AI Stack
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An infographic compares Tokenmaxxing and Inference Yield leaderboards, showing top performers change as metrics shift. Tokenmaxxing lists Alex Kim, Taylor Morgan, Jamie Patel; Inference Yield lists Maya Johnson, Jordan Lee, Priya Shah.
Graph + AI
Thu 16 Apr 2026
Tokenmaxxing is a Phase. Inference Yield is the Strategy.
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Infographic compares Vector RAG and GraphRAG token usage: scattered blue dots (high compute/power) vs. connected orange nodes (lower compute/power). Learn how to reduce AI inference cost and tokens—stop wasting resources today!.
Graph + AI
Mon 13 Apr 2026
AI Is Facing a 19-Gigawatt Power Gap. Here’s the Fix.
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A graphic shows icons for fraud signals and connected network devices, with the text: More Fraud Signals Will Not Save You. Connections Will. The TigerGraph logo appears in the top left corner.
Fraud / Anti-Money Laundering, Graph Databases
Fri 10 Apr 2026
More Fraud Signals Will Not Save You. Connections Will.
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An infographic by TigerGraph shows how graph technology benefits retail—fraud detection, demand forecasting, supply chain visibility—and healthcare—referral optimization, medication safety, care coordination—beyond recommendations.
Fraud / Anti-Money Laundering, Graph Databases, Healthcare
Fri 10 Apr 2026
What Graph can do for Retail and Healthcare, Beyond Recommendations
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Infographic titled How Over-Resolved Entities Suppress Alerts shows user icons linked to institutions with alert symbols, merging into overlapping circles labeled Multiple Signals. TigerGraph logo is at the top left.
Entity Resolution, Fraud / Anti-Money Laundering, Graph Databases
Thu 9 Apr 2026
How Over-Resolved Entities Suppress Alerts 
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