A unified and governed layer provides data, semantics, context and policies to dashboards, applications, assistants and autonomous agents, without companies having to rebuild their data infrastructure for each use case
GoodData.AI, the open platform for agentic analytics, has announced today the launch of Agentic Serving Plane, a governed execution layer designed for high-concurrency data workloads and with a high contextual component generated by artificial intelligence agents.
Agentic Serving Plane sits between enterprise data platforms and the applications, analytical experiences and agents that consume their data. It provides processing services for workloads, enterprise semantics, contextualization, access control and AI execution through a common governed layer.
The current enterprise data infrastructure was designed mainly for people: occasional queries, predictable workloads and access by known users. AI agents work differently. A single business task can generate dozens or hundreds of short-duration data operations while an agent investigates, reasons and decides what to query next. When many agents operate simultaneously, intermittent human queries turn into a continuous, high-concurrency agentic demand.
Agents also need more than raw data. They require business definitions, relationships, permissions, policies and specific context for each task in each request. Without a service layer designed for these workloads, agent-generated traffic can slow down, become costly or cause disruptions in the underlying data platforms.
At the same time, the enterprise data technology ecosystem is becoming increasingly fragmented. Cloud data warehouses and lakehouse platforms increasingly incorporate their own compute, semantics and artificial intelligence capabilities, while companies often operate with multiple data platforms, applications and analytical environments.
The result is a new infrastructure need: a common layer that maintains coherence of business definitions, isolates automated workloads, applies access policies, and provides a governed context, regardless of where the underlying data resides.
"For years, the market evaluated business intelligence (BI) by its dashboards. Underneath them, GoodData.AI was developing a governed system to provide data to applications: semantics, certified metrics, query planning, caching, permissions, and isolation between customers. With artificial intelligence, these capabilities become the product itself," notes Roman Stanek, CEO and founder of GoodData.AI.
Business value for organizations
Agentic Serving Plane supports the different ways in which people and systems consume business data, from dashboards and embedded applications to assistants, copilots, and autonomous agents.
Companies can use the same governed infrastructure to develop internal analytics solutions, operational AI applications, customer-oriented data products, and premium services based on artificial intelligence.
Agents can incorporate analytics directly into operational workflows, investigate business situations across multiple steps, and progressively automate follow-up actions. Analytics applications and experiences can reuse the same business definitions, permissions, and execution services.
Since each new application or agent uses the same underlying service capabilities, semantics, context, and governance, teams do not need to rebuild the data infrastructure for each use case. This can shorten development cycles, reduce infrastructure duplication, and provide enterprise IT departments with a common control layer for analytical and artificial intelligence workloads.
How Agentic Serving Plane works
Agentic Serving Plane is designed to work with the data infrastructure that companies already use.
Through open technologies, such as Apache Iceberg and Apache Arrow, GoodData.AI can handle analytical workloads and agent workloads from data environments controlled by customers, incorporating the semantic, contextual, governance, and execution capabilities that both people and AI systems need.
For example, an agent investigating a drop in revenue can begin by comparing regions, then examining product lines, and finally identifying individual accounts, so that each result determines the next query.
The Agentic Serving Plane manages this sequence as a governed workload. It applies the corresponding business definitions and access policies to each request, isolates agent traffic from other workloads, and is designed to maintain consistent performance in processing queries as the volume of automatically generated requests increases.
The architecture is based on the technology that GoodData.AI has developed since its founding for software companies that integrate analytical capabilities into their own products, enabling numerous customers to share a single platform while the data, permissions, and business contexts of each remain isolated.
Gartner recognized GoodData.AI as a visionary company in the Magic Quadrant™ of Gartner® for 2026 for analytics and business intelligence platforms, highlighting the company’s broader approach to analytical and developer-oriented platforms.
About GoodData.AI
GoodData.AI is an open agential analytics platform that helps businesses apply artificial intelligence to their data, while maintaining control over business definitions, permissions, and execution context.
Its agents can carry out multi-step business processes, rather than being limited to answering a single question and stopping. Its analyses and actions are grounded in the semantics, policies, and context defined by customers, so that organizations retain control over how business data is interpreted and used.
For more information, visit GoodData.AI.