Arango Showcases Live Contextual Data Layer for Enterprise AI at Snowflake Summit 2026

Attendees will learn how to transform fragmented enterprise data into connected business context — enabling AI agents, assistants, and applications to reason, decide, and act reliably at scale

SAN FRANCISCO--(BUSINESS WIRE)--Arango today announced it will showcase Arango AutoGraph and preview Arango Virtual Graph at Snowflake Summit 2026, two capabilities of the Arango Contextual Data Platform that help organizations create an always-on Live Contextual Data Layer for enterprise AI. Together, these capabilities help organizations build connected business context once and make it continuously available across enterprise-wide AI initiatives.

Despite historic investments in AI models, data infrastructure, and analytics platforms, most enterprises continue to struggle to convert AI initiatives into measurable business outcomes. The barrier is not data volume—it is business context. Critical business knowledge remains fragmented across enterprise systems, applications, databases, and documents. The result is AI that is expensive to build, difficult to govern, and unreliable at scale.

“Enterprise AI only creates business value when it can reason, decide, and act in the context of how the business actually works,” said Ravi Marwaha, COO and Chief Product & Technology Officer, Arango. “Today, most organizations rebuild that business context every time an AI agent, application, or workflow needs it. That approach is expensive, difficult to scale, and increasingly unsustainable. The organizations that succeed with AI will treat business context as a reusable strategic asset, built once and shared continuously across AI initiatives.”

Build the Live Contextual Data Layer Once. Reuse It Everywhere.

Most enterprise AI initiatives rebuild business context for every agent, application, and workflow, creating duplicated infrastructure, fragmented governance, and escalating costs. The Arango Contextual Data Platform takes a different approach, treating business context as a shared organizational asset rather than a per-project cost.

Organizations can build a persistent Live Contextual Data Layer, a continuously updated, governed representation of how their business actually works, and reuse it across AI initiatives. Built on a graph-native multimodel foundation, the platform eliminates the integration complexity, data synchronization overhead, and governance gaps that arise when graph, vector, retrieval, and AI infrastructure are assembled from separate point solutions.

The Live Contextual Data Layer:

• Connects structured, semi-structured, and unstructured data across enterprise sources
• Understands entities, relationships, and the policies and events that govern them
• Enables accurate retrieval through both GraphRAG and VectorRAG
• Enforces governance through end-to-end lineage and role-based access controls
• Persists organizational knowledge as a continuously evolving source of operational truth

The result is enterprise AI that delivers more accurate responses, faster decision cycles, stronger governance, lower operational complexity, and compounding return on AI investment over time.

Arango AutoGraph: Automatically Build Live Context for Enterprise AI

Arango AutoGraph eliminates the most expensive and time-consuming phase of enterprise AI development: building the knowledge graph. Traditionally, graph construction requires months of manual schema design, entity modeling, relationship mapping, and pipeline engineering.

At Snowflake Summit 2026, Arango will demonstrate how AutoGraph connects business context across customers, products, operations, documents, and enterprise systems, enabling organizations to accelerate from fragmented data to production-grade AI in days rather than months without requiring specialized graph expertise or manual construction work.

Arango AutoGraph capabilities include:

• Automated entity and relationship discovery across enterprise data sources
• Continuous graph construction and enrichment as business context evolves
• Unified context for GraphRAG, VectorRAG, and agent memory
• End-to-end lineage and governance from source data to AI response
• No-code Knowledge Graph construction — no graph expertise required

Arango Virtual Graph for Snowflake: Live Context Without Moving Your Data

Arango is previewing Arango Virtual Graph for Snowflake, a zero-egress approach to creating a Live Contextual Data Layer for organizations that use Snowflake as their cloud data platform.

Unlike conventional AI architectures that reconstruct context through complex runtime pipelines on every inference call, Arango Virtual Graph establishes a persistent, governed Live Contextual Data Layer that AI agents can access directly. Organizations gain a unified understanding of business context across Snowflake and connected enterprise systems without moving, duplicating, or creating new data silos.

By bringing the Arango Contextual Data Platform and Snowflake Cortex AI together, Virtual Graph enables organizations to maintain Snowflake as their source of truth while providing the context orchestration enterprise AI requires. The result is lower infrastructure costs, simpler architectures, stronger governance, and faster access to trusted business context.

Arango Virtual Graph capabilities include:

• Zero-egress Live Contextual Data Layer — all data remains inside Snowflake
• Unified context across Snowflake tables and connected enterprise sources
• Persistent, governed contextual data layer — no runtime context reconstruction
• Snowflake Cortex AI integration: Cortex Analyst, Cortex Search, and Snowflake Intelligence
• Data residency and governance policy enforcement across all AI interactions

“Snowflake customers understand that their data is their most strategic asset,” said Ravi. “Arango Virtual Graph extends that investment directly into the AI layer, connecting the business context held in Snowflake with the reasoning capabilities that enterprise AI demands, without moving a row of data.”

Meet Arango at Snowflake Summit 2026

Arango invites Snowflake Summit attendees to experience how the Live Contextual Data Layer transforms enterprise AI investments into business outcomes:

• Live demo: Arango AutoGraph — Automatically Build Live Context for AI
• Preview demo: Arango Virtual Graph — Bring Context to AI Without Moving Your Snowflake Data
• Get the new ebook: The Contextual Data Layer for Enterprise AI: 6 Architectural Requirements for Building Agentic-AI-Ready Systems
• Book a meeting with Arango’s contextual data architects

About Arango

Arango is pioneering the Live Contextual Data Layer for enterprise AI, helping organizations transform fragmented enterprise data into connected business context that enables AI agents, assistants, and applications to reason, decide, and act reliably at scale.

Built on the Arango Contextual Data Platform, a graph-native multimodel 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 result is more accurate decisions, end-to-end traceability, faster deployment, and measurable business outcomes.

Organizations including NVIDIA, HPE, London Stock Exchange Group, PSI CRO, the U.S. Air Force, NIH, Siemens, Transient.AI, Matpriskollen, and Articul8 rely on Arango to power enterprise AI. Arango is a member of the NVIDIA Inception Program and the AWS ISV Accelerate Program. Learn more at arango.ai.