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Jazz

A 2024-founded New York startup reinventing DLP with an AI Agentic Investigator, backed by Glilot, Team8, and Ten Eleven.

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48/100Emerging / Unranked

Overview

Jazz, founded in 2024 and based in New York, rebuilds data loss prevention around an AI-powered Agentic Investigator that uses a forensic endpoint agent to understand the full context of data behavior, aiming to cut the false positives and blind spots of traditional rule-based DLP.

It raised a Series A from a syndicate including Glilot, Team8, and Ten Eleven. The effectiveness of the agentic-investigator concept is not yet independently proven.

Innovation Matrix Assessment

Innovation Velocity 6/10

Emerged from stealth with $61M combined seed ($18M) and Series A ($43M, announced 2026-03-10/11) led by Glilot Capital Partners and Team8.

Operational Value 3/10

Company just emerged from stealth alongside the funding; named enterprise production deployments were not disclosed in coverage reviewed.

Market Momentum 6/10

$61M raise closed 2026-03-10/11 with Ten Eleven Ventures, MassMutual, and Merlin Ventures joining lead investors Glilot Capital and Team8.

Category Disruption 5/10

Replacing static rule-based DLP policies with an AI-driven forensic endpoint agent that understands data-behavior context is a meaningful architectural shift for the DLP category.

Real-World Efficacy 3/10

No independent validation of false-positive reduction or detection accuracy was located; claims are vendor-sourced at launch.

Enduring Relevance 6/10

AI-era data leakage (including via AI tools and agents) is a fast-rising concern, keeping modernized DLP highly relevant to CISOs.

Why CISOs Should Care

Jazz rebuilds data loss prevention around an AI-powered 'Agentic Investigator' that uses a forensic endpoint agent to understand the full context of data behavior, aiming to cut the false positives and blind spots that have long plagued traditional DLP tools.

What Makes It Different

Applies AI-driven contextual understanding of data behavior (rather than static rules/regex-based DLP policies) via a forensic endpoint agent, aiming to reinvent a notoriously noisy security category.

The Matrix Verdict

48/100 — EMERGING / UNRANKED

Well-funded, credibly-backed re-approach to a legacy DLP problem with a strong investor syndicate (Glilot, Team8, Ten Eleven); efficacy of the 'agentic investigator' concept is not yet independently proven.

Editorial Note: Claims vs. Verified Findings

Funding and platform description verified via Calcalistech, fintech.global, and company blog. DLP accuracy/false-positive-reduction claims are vendor-described.

Sources