Arvind Jain
VERIFIED TECHNICAL DOSSIERSources checked

Arvind Jain

Founder & CEO, Glean | Co-Founder, Rubrik | Former Distinguished Engineer, Google

2 Verified ArtifactsSource Checked & Attributed

Verified Proof of Work Artifacts

2 items cataloged

Each artifact below represents an authenticated research publication, production code repository, or technical architectural framework directly authored or co-created by Arvind Jain. Every entry undergoes editorial source verification.

#1
IMPLEMENTATION Checked Sep 25, 2026

Enterprise Knowledge Graph Grounding for Multi-Source RAG Systems

Architected Glean's enterprise intelligence engine, coupling deep permissions-aware crawling of 100+ SaaS applications with dense vector embeddings and a dynamic enterprise knowledge graph for sub-second grounded generative question answering.

Model & Execution Context:Hybrid sparse-dense retrieval, enterprise permissions ACL enforcement, LLM synthesis.
Scope & Limitations

Maintaining real-time permission sync across complex Active Directory, Okta, and SaaS permission structures introduces significant distributed indexing overhead.

#2
EXPLANATION Checked Sep 25, 2026

Why Search is the Hardest and Most Critical Foundation for Enterprise Generative AI

Authored technical analysis demonstrating that generative LLM outputs in corporate settings are only as accurate as the underlying retrieval precision, detailing why semantic vector search alone fails without enterprise graph metadata.

Model & Execution Context:Vector retrieval, semantic search, precision@k metrics, context window stuffing vs targeted synthesis.
Scope & Limitations

Synthesized enterprise answers risk exposing sensitive internal corporate gossip or draft documents unless strict contextual access filtering is applied.