AI-native analytics platform

AI at every layer
of your data stack

Deliver consistent, trusted AI insights anywhere your users need them.

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<span>AI at every layer</span><br>of your data stack

Meet your AI assistant

Conversational, context-aware, and agentic-ready — anywhere on your data stack.

  • Ask, explore, and build, through a governed, natural-language interface that understands you.
  • Communicate with ease, through business terms, logic, and structure — via context-aware ontologies.
  • Scale efficiently with Model Context Protocol (MCP), which fits your data stack and grows with you.
Understands your business

Understands your business

Built on your semantic layer to align answers with how your teams think and speak.

Secure and private by default

Secure and private by default

Metadata-only AI queries mean that your underlying data stays private at all times.

Composable and embeddable

Composable and embeddable

Ready out-of-the-box or embeddable into your app, with API and white-label support.

Auditable and trustworthy

Auditable and trustworthy

Traceable answers let your team see how they were generated and trust the outcome.

See the GoodData AI Assistant in action

Watch how natural language becomes trusted answers — all inside your analytics experience.

GoodData AI anywhere it’s needed

Provide the power of AI-native analytics directly within user workflows.

AI for analytics solutions

Why use GoodData AI for data-driven decision-making?

Intelligent use of LLMs, SLMs, and traditional ML balances performance, accuracy, and cost, delivering high-quality insights without unnecessary expense.

Technology for the task

Independence from the traditional BI environment means analytics AI can be delivered directly to user workflows.

Standalone capability

Customizable to data product needs thanks to a modular design, API-driven architecture, and embeddable components.

Flexible and customizable

Reduced reliance on high-cost AI models for simpler tasks, ensures optimal resource allocation and lower total cost of ownership.

API-level integration

Intuitive natural language interfaces and semantic search make analytics insights accessible to all, from engineer to consumer.

Democratized data access
Technology for the task
Standalone capability
Flexible and customizable
API-level integration
Democratized data access
Get started with GoodData AI icon

Get started with GoodData AI

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What’s on the roadmap?

AI metadata creator

Auto-generate business-friendly descriptions and metadata for semantic layer objects.

Analytics as Code + Cursor

Explore next-gen AI workflows driven by semantic context and code-first analytics orchestration.

Auto-generated data stories

Turn complex data analysis into easy-to-understand narratives customized for your users.

Model Context Protocol (MCP)

Test real-time context sharing between AI tools and your semantic layer using our upcoming SDK.

Key drivers and explainability

Identify and explain key factors influencing data points, metrics, and trends.

AI-curated content

Deliver a tailored home page experience based on your users’ activity trends and interests.

AI you can trust

Get a real-world look at how GoodData makes AI in analytics explainable, embeddable, and safe for enterprise teams.

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AI you can trust

Common questions

GoodData AI Assistant is your personal AI analyst — a conversational interface that lets you ask questions in natural language and get accurate, explainable insights. Powered by your semantic layer and business logic, it delivers answers that are governed, consistent, and ready for production use — not just demos. It's built to work across dashboards, apps, and embedded workflows.

Smart Search is a natural language search feature that lets users instantly locate dashboards, visualizations, and metrics across their workspace — even with partial matches or synonyms. It uses AI to go beyond keyword search, helping users find the right insights faster and with minimal friction.

Together, these features are part of GoodData AI — a composable, explainable, and secure analytics layer that aims to bring AI to every level of the data stack.

GoodData implements comprehensive privacy and security control, role-based access control (RBAC), and audit logs to track data access and changes. These measures ensure compliance with industry standards like GDPR and HIPAA.

GoodData's platform ensures accuracy through advanced data governance features, including version control, data lineage tracking, and strict validation checks before processing. Additionally, AI-powered features are regularly fine-tuned to ensure reliable and consistent outputs.  Because of the bounds that the semantic layer provides, the LLM is much less likely to hallucinate compared to AI assistants that do not have such bounds.

The use of retrieval augmented generation (RAG) means that the LLM doesn’t calculate the data but instead generates JSON files/text response. In turn, this ensures that OpenAI doesn’t see specific data, only the metadata, and GenAI creates JSON from this and passes it back into our system. Calculations are then carried out on GoodData’s side, minimizing the risk of hallucination.

Yes, GoodData's platform is highly flexible and can handle complex, custom data schemas. It supports a wide range of data sources and formats, allowing you to integrate and model your specific datasets with ease.