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Jube vs Quantexa Entity Resolution

Jube

7.3#3 in financial crime compliance softwareFrom $350 a month
Free planWebAPILinuxSelf-hosted
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What both publish

FactJubeQuantexa Entity Resolution
DeploymentJube is containerized for Docker and Kubernetes, supports multi-tenancy, and can run on an organisation’s own infrastructure or cloud tenancy.The product can be deployed on-premises or in a preferred cloud, and the company FAQ also describes cloud, hybrid and on-premises deployment options.
HeadquartersNottingham, England, UKLondon, United Kingdom
Intended usersThe maker describes Jube as intended for compliance teams, financial institutions, fintechs, and organisations adopting it for AML or fraud detection.Quantexa says the platform is used by enterprises and government agencies and is trusted by banks, insurers, telecoms, healthcare providers and government agencies.
PurposeJube is an open-source platform for real-time suspicious-transaction detection, AML case management, and fraud prevention.Entity Resolution connects disparate and ambiguous data to create 360° views of people, organizations and places.
SupportSupport is async-first over WhatsApp, with Loom video and documentation responses tracked against a permanent record.Quantexa describes customer support through a dedicated Customer Success team, roadmap sessions, a support desk for break-fix issues, training and its Learning Academy.

Jube plans

  • JubeFree
  • Jube softwareFree
  • Sandbox support$350 a month
  • Growth support$950 a month
  • Scale support$1,590 a month
  • Public training (Kuala Lumpur, April 2026)$1,825, paid once

Quantexa Entity Resolution plans

No prices published.

Pick Jube if…

Jube is intended for compliance teams, financial institutions, fintechs, and organizations adopting AML or fraud detection. It suits teams able to manage a self-hosted deployment and account for AGPLv3 obligations.

Pick Quantexa Entity Resolution if…

It suits enterprises and government agencies that need to reconcile records across people, organizations or places. The listed use cases include financial crime, anti-money laundering, customer intelligence and fraud.

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