Author: GoodData

  • Context Management Powers Production-Ready AI Analytics at Enterprise Scale

    Context Management Powers Production-Ready AI Analytics at Enterprise Scale

    GoodData delivers governed semantics, grounded knowledge, guided behavior, and full observability for reliable AI analytics.

    SAN FRANCISCO, CALIFORNIA / ACCESS Newswire / March 12, 2026 / GoodData today introduced Context Management, a governed contextual layer designed to enable production-ready enterprise AI analytics and agents.

    As organizations deploy AI assistants, copilots, and autonomous agents, they encounter a structural gap: AI lacks enforced business context, governance, and observability. AI pilots demonstrate potential, but moving AI into production exposes the deeper challenge of ensuring answers are consistent, safe, and explainable at scale.

    Without semantics and traceability, answers shift depending on phrasing. Business rules are applied inconsistently. When outputs change, teams can’t explain why. For enterprises, this erodes trust and slows adoption.

    Many AI analytics platforms rely on prompts, inferred metadata, or loosely integrated document search. Context is suggested, not enforced.

    GoodData’s Context Management addresses these structural gaps by providing an analytics foundation with a governed contextual layer purpose-built for AI systems. It creates a single access point to structured and unstructured data, business knowledge, policies, and instructions, ensuring AI operates within defined boundaries.

    By formalizing how context is defined, governed, and observed, Context Management improves answer quality, strengthens safety controls, and makes AI behavior transparent in production environments.

    The Five Pillars of GoodData’s Context Management

    Context Management manages meaning, governance, grounding, guidance, and observability, making AI analytics accurate, safe, and explainable in production environments.

    These pillars define the structural requirements for enterprise AI: enabling high-quality responses within reliable systems.

    Data Semantics: Defines metrics, dimensions, and business logic once in a deterministic semantic model. Agents, dashboards, and APIs use the same definitions, so numbers never change based on how a question is asked.

    Governance: Applies enterprise-grade controls to data access, usage policies, and agent behavior. AI operates within defined boundaries by default, preventing misuse, leakage, and unsafe actions.

    Knowledge Grounding: Grounds every response in structured analytics and governed enterprise content. Answers are traceable to their sources, reducing hallucinations and increasing reliability.

    AI Guidance: Provides business instructions, analytical intent, and memory that define how AI should behave, ensuring consistent terminology, priorities, and explanations across users and workflows.

    Observability: Tracks prompts, inputs, outputs, and costs end-to-end. Understand what context was used, what changed, and why results evolved, making AI analytics transparent and auditable.

    A Governed Foundation for Enterprise AI Teams

    Built on GoodData’s composable, embeddable architecture, Context Management integrates with modern data stacks and developer workflows. It supports structured and unstructured data, enables multitenant deployments, and applies governance across assistants, agents, dashboards, and embedded applications.

    “AI pilots are easy. Production-ready AI is hard,” said Peter Fedorocko, Field CTO at GoodData. “Enterprises need answers that are consistent, governed, and explainable. Context Management ensures agentic AI analytics is grounded in the same semantic definitions, business rules, and knowledge that teams rely on every day.”

    For analytics engineers, this means deterministic metrics defined as code and reused consistently across AI and analytics. For enterprise data leaders, it means AI operating within governance boundaries by default. For product and AI teams, it means production-ready agents embedded securely into customer-facing applications.

    A Trusted Foundation for Production-Ready AI

    Context Management extends GoodData’s AI-native platform with a governed contextual layer designed for agentic analytics in production.

    As organizations move from experimentation to operational AI, the need for enforced semantics, grounded knowledge, and decision observability becomes foundational. Context Management provides that foundation.

    With this release, GoodData extends its existing analytics infrastructure with the contextual and governed controls required for enterprise AI systems, where assistants, copilots, and autonomous agents operate with shared meaning, governance, and full transparency.

    About GoodData

    GoodData is an AI-native decision intelligence platform built to help enterprises turn trusted data into confident action. Designed for governed, scalable analytics, GoodData enables organizations to operationalize insights, automate decisions, and embed intelligence directly into products and business workflows.

    With a composable architecture and a governed semantic layer at its core, GoodData ensures AI-powered analytics are transparent, auditable, and aligned with how enterprises define and trust their data. Organizations use GoodData to move from insight to impact faster, while maintaining enterprise-grade security, governance, and performance.

    GoodData serves over 123,000 of the world’s leading companies and 3.9 million users, helping enterprises close the gap between data and decision-making.

    For more information, visit GoodData’s website and follow GoodData on LinkedIn, YouTube, and Medium.

    GoodData Contact:

    press@gooddata.com
    +1 415-200-0186

    © 2026 GoodData Corporation. All rights reserved. GoodData is a registered trademark of GoodData Corporation in the United States and other jurisdictions. Other names and brands may be claimed as the property of others.

    SOURCE: GoodData

    View the original press release on ACCESS Newswire

  • GoodData Brings Faster BI Modernization to Make Analytics AI-Ready

    GoodData Brings Faster BI Modernization to Make Analytics AI-Ready

    Modernize legacy BI without disruption. Refactor business logic into a governed semantic layer while keeping dashboards online.

    SAN FRANCISCO, CALIFORNIA / ACCESS Newswire / January 28, 2026 / GoodData, the AI-powered analytics and decision intelligence platform, today introduced AI-driven BI modernization, a new approach that helps organizations move off legacy BI faster while preserving critical reporting workflows.

    Early outcomes teams can expect

    AI-driven BI modernization separates business logic from dashboards and standardizes it in a governed semantic layer. This improves performance today and creates a stronger baseline for AI-driven use cases tomorrow.

    Expected results include:

    • 2-5× faster iteration cycles for delivering new analytics

    • Dashboards that load up to 10× faster by removing inefficient calculations and duplication

    • Consistent, reusable metrics governed centrally and applied across teams and tools

    • AI-ready analytics with clean, standardized logic that AI agents and automation can query reliably

    Why BI modernization keeps getting stuck

    For many enterprises, BI has become harder to maintain and harder to trust. Over time, business logic gets distributed across dashboards, SQL, and spreadsheets. What once felt flexible becomes fragile. It’s expensive to maintain, difficult to govern, and risky to change. Teams spend significant budget keeping legacy BI running, while different dashboards quietly produce different versions of the truth.

    That fragmentation becomes a major barrier to AI adoption. When metric logic is buried inside BI tools and inconsistently defined, even basic questions become hard to answer with confidence. If your team can’t explain how a number is calculated, AI won’t be able to either.

    A faster, safer way to modernize without starting over

    Modernization doesn’t need to mean ripping everything out and waiting a year to see value. GoodData takes a phased approach that keeps dashboards online while the foundation is improved underneath.

    Instead of forcing a rebuild, we create a bridge that uses AI to extract and refactor BI logic from legacy BI tools. It identifies broken logic, unused metrics, and duplication during migration. This prevents teams from recreating the same complexity in a new environment.

    “Teams don’t have time for multi-quarter rebuilds that slow decision-making,” said Roman Stanek, CEO and Founder of GoodData. “They want to keep the business moving and ship analytics changes faster. With GoodData, you don’t just migrate. You fix what’s holding you back. This approach gives enterprises the velocity to modernize while staying in control of the numbers their teams depend on.”

    How AI-driven BI modernization works with GoodData

    GoodData modernizes BI by extracting and restructuring business logic from existing tools into a governed foundation that scales across teams, use cases, and AI systems.

    The approach includes:

    • Extracting BI logic with AI, capturing calculations, filters, joins, and metric definitions independently of dashboard layouts

    • Refactoring and standardizing logic to remove unused metrics, consolidate duplicates, and reduce technical debt

    • Building a governed semantic layer organized using a medallion architecture, with clear lineage and reusable definitions

    • Deploying analytics-as-code by converting logic into version-controlled YAML files that support testing, reviews, and fast rollbacks

    What this enables next

    As organizations move from dashboard-driven analytics to AI-assisted decision-making and autonomous AI agents, trust and consistency become non-negotiable. GoodData helps teams modernize with less disruption and more control. The result is a governed layer of business logic that can serve reporting, embedded analytics, and AI experiences from the same foundation. Teams move faster, definitions stay consistent, and analytics remain reliable as adoption scales.

    About GoodData

    GoodData is an AI-native decision intelligence platform built to help enterprises turn trusted data into confident action. Designed for governed, scalable analytics, GoodData enables organizations to operationalize insights, automate decisions, and embed intelligence directly into products and business workflows.

    With a composable architecture and a governed semantic layer at its core, GoodData ensures AI-powered analytics are transparent, auditable, and aligned with how enterprises define and trust their data. Organizations use GoodData to move from insight to impact faster, while maintaining enterprise-grade security, governance, and performance.

    GoodData serves over 140,000 of the world’s leading companies and 3.2 million users, helping enterprises close the gap between data and decision-making.

    For more information, visit GoodData’s website and follow GoodData on LinkedIn, YouTube, and Medium.

    Press contact:

    press@gooddata.com
    +1 415-200-0186

    © 2026 GoodData Corporation. All rights reserved. GoodData is a registered trademark of GoodData Corporation in the United States and other jurisdictions. Other names and brands may be claimed as the property of others.

    SOURCE: GoodData Corporation

    View the original press release on ACCESS Newswire

  • GoodData Announces Launch of MCP Server to Let AI Execute Analytics End-To-End

    GoodData Announces Launch of MCP Server to Let AI Execute Analytics End-To-End

    Combining MCP, analytics-as-code, and LLMs to automate analytics execution at software speed

    SAN FRANCISCO, CALIFORNIA / ACCESS Newswire / January 21, 2026 / GoodData, a leader in AI analytics and decision intelligence, today announced the public launch of its MCP Server. As organisations adopt AI in analytics, most tools remain limited to query generation, leaving teams to manually manage metrics, dashboards and business logic. MCP Server moves AI beyond analysis, enabling governed, end-to-end analytics execution and delivering 10-50x faster time to value.

    The MCP Server is designed for AI developers, and BI and data teams who want to build and manage analytics faster with AI. It allows AI to build and operate analytics in the same way a skilled human team would, but faster and without operational bottlenecks.

    Using the Model Context Protocol (MCP), AI agents and large language models (LLMs) can connect directly to GoodData and execute analytics across the full lifecycle. They can work with governed analytics assets, including semantic models, metrics, dashboards and alerts, without relying on screenshots, SQL copy-and-paste or fragile UI workflows. In practice, this means AI can build, update and run analytics processes and agentic workflows automatically, while respecting the same rules and controls as human users.

    “Analytics has never been limited by questions, it’s been limited by execution,” said Roman Stanek, CEO and Founder of GoodData. “With MCP Server, we’re turning analytics into an executable system that AI can safely operate under governance. This fundamentally changes how fast organisations can build, adapt and scale AI analytics.”

    From AI-assisted analysis to analytics execution

    GoodData’s MCP Server shifts AI from interacting with analytics to executing within it. Rather than layering AI on top of dashboards or query interfaces, MCP exposes analytics as executable infrastructure.

    By combining analytics-as-code, governed APIs and LLM-based coding, MCP Server allows AI to create, modify and validate analytics assets directly. Definitions remain consistent as they evolve, analysis runs continuously and changes propagate safely, without requiring manual intervention at every step.

    All execution takes place under the same security, permissions and governance model used by human teams. Business rules are enforced by the system rather than relying on individual knowledge, reducing operational risk while increasing speed and reliability.

    How teams use MCP Server

    With MCP Server, analytics and BI assets become programmatic resources that AI can work with directly:

    • Accelerate BI development with AI: Analytics-as-code allows AI to build and update analytics automatically, reducing BI backlogs and eliminating manual UI-driven work.

    • Enable continuous AI-driven analysis: Once analytics are defined, execution is ongoing, data is queried, results are computed, dashboards are updated, alerts are scheduled and logic remains in sync.

    • Extend analytics to any AI agent: Any MCP-compatible agent can safely use GoodData’s full analytics capabilities, modelling, metrics, queries, alerts and validations, under the same governance controls as human experts.

    “GoodData’s MCP Server turns analytics assets, such as semantic models, metrics and dashboards, into software resources,” said Peter Fedorocko, Field CTO at GoodData. “Any AI agent can work with them using the same APIs, permissions and governance controls as engineering teams, delivering 10-50x faster time to value.”

    Why this works now

    This shift is possible because three advances have converged: MCP provides a standard execution layer for AI, analytics-as-code makes analytics programmable, and modern LLMs can reliably operate complex systems within defined constraints. Together, they transform analytics execution from a linear, people-bound process into a scalable platform capability.

    About GoodData

    GoodData is an AI-native decision intelligence platform built to help enterprises turn trusted data into confident action. Designed for governed, scalable analytics, GoodData enables organizations to operationalize insights, automate decisions, and embed intelligence directly into products and business workflows.

    With a composable architecture and a governed semantic layer at its core, GoodData ensures AI-powered analytics are transparent, auditable, and aligned with how enterprises define and trust their data. Organizations use GoodData to move from insight to impact faster, while maintaining enterprise-grade security, governance, and performance.

    GoodData serves over 140,000 of the world’s leading companies and 3.2 million users, helping enterprises close the gap between data and decision-making.

    For more information, visit GoodData’s website and follow GoodData on LinkedIn, YouTube, and Medium.

    Contact:

    +1 415-200-0186
    press@gooddata.com

    SOURCE: GoodData

    View the original press release on ACCESS Newswire

  • GoodData Accelerates in Q4 with Product Innovation and Business Growth

    GoodData Accelerates in Q4 with Product Innovation and Business Growth

    SAN FRANCISCO, CALIFORNIA / ACCESS Newswire / January 15, 2026 / GoodData, a leading AI-native decision intelligence platform, today announced strong Q4 results driven by record product development velocity, the launch of its Intelligence Layer for trustworthy AI, and continued expansion across the financial services sector.

    The quarter underscored GoodData’s commitment to delivering inclusive, governed AI at scale, marked by significant accessibility milestones and sustained adoption among global enterprises.

    Business highlights

    GoodData’s momentum accelerated throughout Q4, fuelled by a surge in development activity and deepening strategic partnerships. The company delivered a 50% year-on-year increase of product releases in Q4 2025 compared to Q4 2024, with a three-fold increase in AI-focused development activity in agentic workflows in H2.

    “Our performance in Q4 shows that speed and trust are not mutually exclusive,” said Roman Stanek, CEO and Founder of GoodData. “With the launch of the Intelligence Layer and our focus on accessibility and governance, we are giving enterprises the guardrails they need to embrace agentic AI. A 296% increase in AI development activity demonstrates the velocity at which we are moving to help customers turn data into intelligent action.”

    Strategic enterprise deployments delivered strong growth. In a major global rollout for a strategic payments partner, GoodData onboarded more than 2,000 client organisations and 13,600 users. The deployment achieved a 40% higher activation rate and generated 27 times user growth in the MEA region, laying the foundation for continued expansion in 2026.

    Product innovation

    Q4 was marked by GoodData’s launch of its Intelligence Layer, designed to unify governed, trustworthy AI analytics across enterprise data environments and enable organizations to operationalize AI with confidence and consistency.

    The release introduced new tools to strengthen trust and governance, including the Analytics Catalog, which simplifies asset discovery and management, and the Semantic Quality Agent, which continuously assesses and improves semantic layer accuracy. GoodData also introduced AI Memory, enabling analytics experiences to incorporate historical context and deepen decision confidence.

    Analytical capabilities were further enhanced with Key Driver Analysis, allowing users to identify the factors influencing business metrics, and Aggregate Awareness, which improves performance by automatically leveraging pre-aggregated data.

    Accessibility remained a core focus throughout the quarter. GoodData published an independent Accessibility Conformance Report confirming that GoodData Cloud aligns with WCAG 2.1 Level AA, Section 508 and EN 301 549, reinforcing its commitment to inclusive analytics.

    Additional milestones

    Industry-specific innovation continued with the debut of Agentic AI for Financial Services, delivering compliant, audit-ready AI agents for fraud detection, regulatory reporting and more. This was reinforced by GoodData’s expanded presence at Money20/20 in Las Vegas.

    The company also strengthened its leadership team with the appointment of Tom Strachan to lead the US market, supporting the expansion of GoodData’s enterprise AI sales footprint.

    About GoodData

    GoodData is an AI-native decision intelligence platform built to help enterprises turn trusted data into confident action. Designed for governed, scalable analytics, GoodData enables organizations to operationalize insights, automate decisions, and embed intelligence directly into products and business workflows.

    With a composable architecture and a governed semantic layer at its core, GoodData ensures AI-powered analytics are transparent, auditable, and aligned with how enterprises define and trust their data. Organizations use GoodData to move from insight to impact faster, while maintaining enterprise-grade security, governance, and performance.

    GoodData serves over 140,000 of the world’s leading companies and 3.2 million users, helping enterprises close the gap between data and decision-making.

    For more information, visit GoodData’s website and follow GoodData on LinkedIn, YouTube, and Medium.

    © 2026 GoodData Corporation. All rights reserved. GoodData is a registered trademark of GoodData Corporation in the United States and other jurisdictions. Other names and brands may be claimed as the property of others.

    Contact:

    +1 415-200-0186
    press@gooddata.com

    SOURCE: GoodData

    View the original press release on ACCESS Newswire

  • GoodData Ushers in Era of Governed and Trustworthy AI Analytics

    GoodData Ushers in Era of Governed and Trustworthy AI Analytics

    New Intelligence Layer allows enterprises to ground AI in governed data, ensuring precision, explainability, and confidence in every decision.

    SAN FRANCISCO, CA / ACCESS Newswire / December 3, 2025 / GoodData, leader in AI analytics and data intelligence, today announced the launch of its Intelligence Layer, a suite of governed, context-aware AI capabilities that bridge the gap between raw data and trustworthy, action-ready intelligence. Built for organizations operating across complex data environments, whether on-premises or across cloud services, the Intelligence Layer ensures that AI is grounded in a company’s own rules, logic, and semantic definitions.

    Roman Stanek, CEO of GoodData, says: “Most companies don’t need more dashboards; they need clarity. They need to know their data is right, easy to understand, and ready to use. That’s exactly what the Intelligence Layer is built for.”

    The Intelligence Layer embeds governance and business context directly into the analytical process, closing the gap between complex data architectures and the everyday decisions business users make. Untethered AI agents frequently and unpredictably run into issues with data permissions and model context, limiting their effectiveness. Grounding AI in an organization’s own rules, logic, and definitions, GoodData transforms traditional reporting into a system where insights naturally flow into action and strengthen critical business processes.

    Analytics into action

    At the heart of this new layer is the Analytics Catalog, a unified workspace where teams can explore and control their analytical definitions. Instead of juggling scattered metrics or debating which numbers are correct, users can rely on a governed environment supported by AI copilots that help generate and validate analytics objects – dashboards, visualizations, metrics, attributes, facts, and datasets – with precision. The result is a consistent foundation that ensures everyone is speaking the same analytical language.

    Complementing the Catalog is the Semantic Quality Agent, which acts as a watchdog for the semantic layer. This automated system scans for inconsistencies, missing context, and ambiguous definitions that can quietly distort AI-generated answers. By continually safeguarding metadata quality, the Agent helps organizations maintain the integrity of their analytics and prevents issues before they surface in dashboards, tools, or AI outputs.

    AI trust and accountability

    Rounding out the Intelligence Layer is AI Memory, a capability that allows organizations to teach their AI Assistant to understand and use their specific terminology, acronyms, and operational nuances. AI Memory also allows teams to customize the assistant’s tone, name, and role, integrating AI seamlessly into their product experience. Rather than offering generic answers, the assistant is equipped to respond in the exact context of the business, ensuring that insights are aligned with how the company truly operates.

    Stanek continues: “AI shouldn’t feel like a black box. It should feel like a part of your team, one that understands your terminology, your priorities, and your guardrails. Together, these elements form a governed, context-aware intelligence system that elevates analytics from passive reporting to an active driver of decision-making. With the Intelligence Layer, people can finally trust the answers they’re getting; they can make decisions faster and with a lot more confidence.”

    About GoodData

    GoodData is a full-stack, AI-native data intelligence platform built for speed, scale, and trust. Its composable platform is designed to empower every enterprise to transform governed insights into action and integrate seamlessly into any data environment across public, private, on-premises, or hybrid cloud. With no-code interfaces, SDKs, and powerful APIs, GoodData supports the full analytics lifecycle from data modeling to AI-powered insights.

    GoodData enables companies to customize flexibly, deploy fast, and monetize new applications and automations – all with enterprise-grade security and governance to embed AI into a range of products. GoodData serves over 140,000 of the world’s top companies and 3.2 million users, helping them drive meaningful change and maximize the value of their data.

    For more information, visit GoodData’s website and follow GoodData on LinkedIn, YouTube, and Medium.

    GoodData Contact

    press@gooddata.com

    ©2025, GoodData Corporation. All rights reserved. GoodData and the GoodData logo are registered trademarks of GoodData Corporation in the United States and other jurisdictions. Other names used herein may be trademarks of their respective owners.

    SOURCE: GoodData

    View the original press release on ACCESS Newswire

  • GoodData Brings AI-Native Data Intelligence to Financial Services

    Embeddable, compliant, and auditable AI agents unlock trusted automation for banks, insurers, and financial institutions.

    SAN FRANCISCO, CA / ACCESS Newswire / October 28, 2025 / GoodData, a leading analytics and data intelligence company, today unveiled new finance-focused applications for its composable AI platform, designed to tackle the industry’s toughest challenges. By combining its AI Lake, AI Hub, and AI Apps into a single foundation for enterprise data intelligence, the next-generation platform gives financial institutions powerful tools to build and deploy AI agents.

    These agents can detect and investigate fraud in seconds with audit trails regulators can trust, keeping portfolios compliant in real time within industry guidelines. This streamlines regulatory reporting by compiling, checking, and submitting disclosures transparently, all while meeting strict standards for financial compliance, governance, and security.

    Purpose-built for finance

    The financial services sector faces unique challenges, from strict regulations and legacy systems to siloed data and rising expectations for modern client experiences. GoodData’s layered platform is designed to meet these needs head-on:

    • AI Lake: Turns structured and unstructured financial data into a governed semantic layer, grounding AI agents in accurate, compliant, and context-aware knowledge for better decision-making.

    • AI Hub: Delivers orchestration and governance with built-in guardrails, escalation paths, and compliance workflows, ensuring safe, auditable AI operations that align with financial regulations.

    • AI Apps: Embeddable agents, copilots, and automations that enhance client-facing applications (like personalized financial advice or onboarding) and back-office functions (like regulatory reporting or fraud detection).

    Benefits for financial institutions

    The platform ensures regulatory compliance and auditability through semantic grounding, detailed audit trails, and robust compliance controls that reduce black-box risk and help meet transparency requirements. Its scalable, multitenant architecture enables seamless expansion across business units, geographies, and client bases.

    Designed to work with both legacy banking systems and modern cloud infrastructures, it is capable of supporting bring-your-own LLMs and deployment in SaaS, on-premise, or hybrid environments – while its developer-friendly SDKs and APIs accelerate time to value for AI-powered products and services.

    “Financial institutions face some of the world’s strictest data governance rules, and our goal is to make compliance simpler,” said Roman Stanek, CEO of GoodData. “This platform lets them innovate with AI while ensuring transparency, trust, and regulatory alignment, modernising client experiences and improving risk management without compromise.”

    The tech behind GoodData’s AI

    At the core is a developer-focused stack that balances compliance with innovation:

    • MCP Server: Manages fast-moving financial processes in real time, while keeping governance in check.

    • SDKs and APIs: Easy-to-use tools (Python, React, APIs) make it simple to add AI agents to apps and internal banking systems.

    • Flexible by design: Open architecture works with existing fintech and banking systems, avoids vendor lock-in, and adapts to changing regulations.

    • Ready to embed: AI copilots, agents, and assistants can be seamlessly added to financial platforms, apps, and dashboards, with your own branding.

    AI-native finance

    GoodData is taking another step into AI-native data intelligence, helping financial institutions move past traditional dashboards and siloed reports toward autonomous, AI-driven services. By combining governance, scalability, and AI innovation in a single platform, GoodData allows banks, insurers, and asset managers to deliver faster results, build stronger client trust, and uncover new revenue opportunities in an increasingly AI-powered financial world.

    GoodData will be exhibiting at Money20/20 USA (Booth #20093), October 26-29th.

    [Ends]

    About GoodData

    GoodData is a full-stack, AI-native data intelligence platform built for speed, scale, and trust. Its composable platform is designed to empower every enterprise to transform governed insights into action and integrate seamlessly into any data environment across public, private, on-premises, or hybrid cloud. With no-code interfaces, SDKs, and powerful APIs, GoodData supports the full analytics lifecycle from data modeling to AI-powered insights.

    GoodData enables companies to customize flexibly, deploy fast, and monetize new applications and automations – all with enterprise-grade security and governance to embed AI into a range of products. GoodData serves over 140,000 of the world’s top companies and 3.2 million users, helping them drive meaningful change and maximize the value of their data.

    For more information, visit GoodData’s website and follow GoodData on LinkedIn, YouTube, and Medium.

    GoodData Contact

    press@gooddata.com

    ©2025, GoodData Corporation. All rights reserved. GoodData and the GoodData logo are registered trademarks of GoodData Corporation in the United States and other jurisdictions. Other names used herein may be trademarks of their respective owners.

    SOURCE: GoodData

    View the original press release on ACCESS Newswire

  • GoodData Reports Record Q3 Growth as It Expands AI Leadership

    SAN FRANCISCO, CA / ACCESS Newswire / October 15, 2025 / GoodData, a leading analytics and data intelligence company, today announced record Q3 results driven by its strongest net new sales ever, the acquisition of Understand Labs, and the launch of its new Full-Stack Intelligence Platform. The quarter underscored the company’s accelerating enterprise adoption, growing international footprint, and continued investment in AI innovation.

    Business highlights

    GoodData’s momentum continued to build in Q3, delivering its best-ever net new annual recurring revenue (ARR) performance. Enterprise engagement was a key driver of this success, with 90% of enterprise opportunities now progressing toward AI and agentic deployments.

    GoodData’s acquisition of Understand Labs, a leader in semantic AI and natural language processing, further strengthened its AI-native capabilities. The addition of Understand Labs’ technology will enhance the intelligence of GoodData’s platform, enabling more natural, conversational analytics and deeper automation across agentic workflows.

    Product innovation

    Towards the end of Q3, GoodData launched its Full-Stack Data Intelligence Platform, unifying its AI Lake, AI Hub, and AI Apps into a single foundation for enterprise AI. It marks a major step in GoodData’s evolution from business intelligence to AI-native data intelligence – helping organisations operationalise insights and accelerate the value of their data.

    The platform enables organisations to move beyond dashboards toward governed, embeddable, and agentic AI solutions that can reason, act, and adapt. With a high-performance semantic data layer, orchestration and governance tools, and secure, customisable AI apps, enterprises can build, deploy, and scale AI agents across products and workflows, all with built-in compliance, open APIs, and support for bring-your-own-LLM integrations.

    Other key milestones from the quarter include:

    • Increased AI adoption: Enterprises are increasingly operationalising agentic workflows on GoodData to turn AI and data investments into solid business outcomes.

    • Strategic team expansion: GoodData has grown its U.S. Enterprise AI sales team to meet rising demand for its AI-native analytics solutions.

    • Global reach: The company opened a new Singapore Data Center, expanding coverage and support for customers across the APAC region.

    “Our record-breaking Q3 proves that our AI-native strategy is reshaping the market,” said Roman Stanek, CEO and Founder of GoodData. “With the acquisition of Understand Labs and the launch of our Full-Stack Intelligence Platform, we’re taking important steps toward our mission: empowering enterprises to unlock AI’s full value through governed, scalable, and trusted analytics.”

    GoodData will be exhibiting at Money20/20 USA (Booth #20093), October 26-29th.

    About GoodData

    GoodData is a full-stack, AI-native data intelligence platform built for speed, scale, and trust. Its composable platform is designed to empower every enterprise to transform governed insights into action and integrate seamlessly into any data environment across public, private, on-premises, or hybrid cloud. With no-code interfaces, SDKs, and powerful APIs, GoodData supports the full analytics lifecycle from data modeling to AI-powered insights.

    GoodData enables companies to customize flexibly, deploy fast, and monetize new applications and automations – all with enterprise-grade security and governance to embed AI into a range of products. GoodData serves over 140,000 of the world’s top companies and 3.2 million users, helping them drive meaningful change and maximize the value of their data.

    For more information, visit GoodData’s website and follow GoodData on LinkedIn, YouTube, and Medium.

    GoodData Contact

    press@gooddata.com

    ©2025, GoodData Corporation. All rights reserved. GoodData and the GoodData logo are registered trademarks of GoodData Corporation in the United States and other jurisdictions. Other names used herein may be trademarks of their respective owners.

    SOURCE: GoodData

    View the original press release on ACCESS Newswire