Arango has been recognized as a Strong Performer in The Forrester Wave: Multimodel Data Platforms, Q2 2026, highlighting the company's growing role in helping organizations build trusted data foundations for enterprise AI. The recognition underscores Arango's native multimodel architecture, customer adoption, and contextual data platform designed to support AI agents, assistants, and intelligent applications with governed and connected business data.
Arango announced that it has been recognized as a Strong Performer in The Forrester Wave: Multimodel Data Platforms, Q2 2026. According to the evaluation, the platform is "well-suited to organizations seeking a contextual data foundation where multihop graph performance and verifiable reasoning are mission-critical for trusted AI."
The company believes the recognition reflects increasing enterprise demand for unified data platforms that simplify how business context is connected, governed, and made available to AI systems. Rather than relying on multiple databases and integration layers, organizations are increasingly adopting consolidated architectures that improve operational efficiency and AI readiness.
Arango's Contextual Data Platform is built on a graph-native multimodel architecture that unifies graph, vector, document, key-value, and search capabilities within a single distributed engine. The platform enables enterprises to create a live Contextual Data Layer that provides a persistent and governed representation of business context for AI applications.
The company stated that the unified platform helps organizations reduce architectural complexity while improving governance, explainability, traceability, and operational scalability across enterprise AI initiatives.
"As organizations move AI initiatives into production, many are discovering that the challenge is no longer simply connecting data. The challenge is creating trusted business context that AI systems can reason over consistently," said Ravi Marwaha, Chief Operating Officer and Chief Product & Technology Officer, Arango. "Enterprises increasingly want a simpler way to build, govern, and operationalize business context across their data landscape. We believe this recognition reflects growing demand for unified platforms that help organizations create a trusted foundation for enterprise AI."
The company noted that enterprises are increasingly prioritizing platforms capable of supporting AI agents, assistants, and intelligent applications through centralized governance, unified data management, and reusable business context. As organizations continue expanding AI deployments, multimodel data platforms are expected to play a key role in improving consistency, reducing duplication, and accelerating production-ready AI solutions.
Arango is pioneering the live Contextual Data Layer for enterprise AI, helping organizations transform fragmented enterprise data into trusted, reusable business context that enables AI agents, assistants, and applications to reason, decide, and act with greater accuracy, explainability, and trust at scale.
Built on the Arango Contextual Data Platform—a graph-native multimodel data foundation that unifies graph, vector, document, key-value, and full-text search capabilities with ACID guarantees—the live Contextual Data Layer enables organizations to build context once and reuse it across AI initiatives.
The platform includes more than 20 built-in AI services for contextual modeling, retrieval, orchestration, and enterprise AI development. The result is more accurate decisions, greater explainability, end-to-end traceability, faster deployment, and increased trust in enterprise AI outcomes.
Organizations including NVIDIA, HPE, Zscaler, London Stock Exchange Group, Siemens, the U.S. Air Force, NIH, Articul8, and others rely on Arango to power enterprise AI.
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