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Hume

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Software Status:Active

About Hume

Hume is a connected data analytics platform from GraphAware that supports intelligence analysis for government-grade applications. It provides a single view of truth, advanced analysis capabilities, and collaborative decision-making so users can achieve fast and intuitive insights. Designed for intelligence professionals, Hume allows users to integrate and analyze complex data efficiently. With capabilities such as simplified intelligence analysis, case studies to guide best practices, and industry-specific applications, Hume facilitates informed decision-making processes. Key capabilities: single view of truth advanced analysis capabilities collaborative decision-making case studies simplified intelligence analysis Best for: intelligence professionals that need to analyze interconnected data efficiently.

Hume Details

Vendor
GraphAware
Year Launched
2013
Location
Graph Aware Limited 86-90 Paul Street London EC2A 4NE United Kingdom
Deployment
cloud, on premise, windows, linux
Training Options
documentation, videos, in person
Countries Served
All Countries
Languages
English
Users
Analysts, Researchers, Statisticians
Industries Served
Law Enforcement, Finance Authorities, National Security
Tags
neo4j, software development, graph databases, machine learning, knowledge graphs, law enforcement, intelligence, graph data science, natural language processing, hume, graph visualisation, analytics, AML, KYC, and recommendations

Hume's In-App Market Place

Does Hume have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

0

Mini Apps

Pricing Options

Free trial
Free version
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Promo Offer

Accepted Payment Currencies

USD ($), EUR (€), GBP (£), JPY (¥), AUD ($), CAD ($), CHF (CHF), CNY (¥), SEK (kr), NZD ($), KRW (₩), RUB (₽)

Pros & Cons

  • Comprehensive platform that unifies ETL, analytics, visualization, and alerting.
  • Visual and low-code tools make complex graph queries and workflows accessible to analysts.
  • Strong NLP integration allows extraction of insights from unstructured text into structured graphs.
  • Advanced querying capabilities through intuitive visual interfaces without needing Cypher or Gremlin.
  • Built for secure and sensitive use cases, including support for SSO, RBAC, and audit logging.
  • Deployment flexibility across cloud, on-premise, and air-gapped environments, suitable for varied IT policies.
  • Best suited for graph-native users; may require infrastructure like Neo4j for full capabilities.
  • Steep learning curve for users unfamiliar with graph modeling or knowledge graph concepts.
  • Enterprise-focused pricing can be a barrier for small or mid-size organizations.
  • Overkill for simple data scenarios where traditional BI tools would suffice.
  • Graph processing can be resource-intensive, requiring strong backend infrastructure for large-scale use.

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