Guandata Showcases DecideX at SCEWC 2026

Guandata highlights its approach to enterprise AI, connecting business context, trusted data, and intelligent agents to help organizations move from insights to informed decisions and measurable action.

BARCELONA, Spain, November 6, 2026 — Guandata, an enterprise AI and business intelligence technology company, participated in Smart City Expo World Congress (SCEWC) 2026, held November 3–5 in Barcelona, Spain, highlighting its DecideX and its vision for the next generation of AI-powered enterprise decision-making.

The event brought together technology providers, industry leaders, and public-sector representatives to explore how emerging technologies can address increasingly complex operational and organizational challenges.

As part of its participation, Guandata introduced its approach to Decision Intelligence, demonstrating how enterprises can build on existing data investments to connect business knowledge, analytical reasoning, and AI-assisted decision processes.

Beyond Data Analysis: Bringing AI into the Decision-Making Process

Organizations have invested heavily in business applications, data infrastructure, and analytical platforms. Yet a persistent challenge remains: access to more information does not automatically translate into better business decisions.

Enterprise data often spans multiple systems, departments, and operational processes. While traditional business intelligence helps organizations understand performance, making effective decisions also requires business context, consistent metrics, analytical reasoning, and the ability to evaluate what happens after an action is taken.

The rapid adoption of generative AI has introduced new possibilities for enterprise analytics. AI agents can interpret natural-language questions, retrieve information, and generate analytical outputs. However, their practical value depends on whether they can understand the business meaning behind the data and provide conclusions that users can verify.

Guandata addresses this challenge through DecideX, designed to help organizations connect existing data assets with business knowledge and decision-making workflows.

Introducing DecideX: Connecting Business Context, AI Reasoning, and Action

DecideX is designed to support enterprise decision-making by combining trusted data, business knowledge, analytical methods, and configurable AI agents.

At the core of the platform is Decision Context, which organizes enterprise business definitions, operational relationships, analytical rules, and relevant knowledge into a structure that AI agents can use to interpret business questions.

This foundation helps agents move beyond isolated data queries toward more contextual analysis.

DecideX supports a connected decision-making process across five stages:

Understand the business problem. Users describe operational challenges in natural language, allowing agents to identify relevant business scenarios and analytical requirements.

Interpret business context. The platform draws on configured business ontologies, metric definitions, business rules, and enterprise knowledge to understand how data relates to actual operations.

Analyze supporting evidence. Agents use authorized data assets and analytical methods to investigate performance changes, identify potential causes, and provide traceable findings.

Recommend next steps. Based on the available evidence and configured business context, DecideX can suggest priorities and follow-up actions for users to evaluate.

Track outcomes and improve. Decision tracking and recurring analysis help organizations review changes over time, evaluate the effects of adopted recommendations, and refine analytical configurations based on feedback.

Through this approach, DecideX aims to make AI-assisted decision-making more transparent, context-aware, and connected to real business processes.

Building a More Reliable Foundation for Enterprise AI

As organizations move from experimenting with AI toward operational adoption, reliability and accountability are becoming increasingly important.

An AI-generated recommendation is only useful when business users can understand the evidence behind it, assess its relevance, and determine whether it should be acted upon.

DecideX addresses these requirements through several complementary capabilities.

Business Ontology provides a structured representation of business objects, relationships, risks, actions, and operational questions. This helps AI agents interpret data within the context of how an organization operates.

Decision Evidence Chains allow users to examine the data sources, metric definitions, analytical steps, and business reasoning associated with AI-generated conclusions.

Decision Tracking enables users to monitor relevant indicators after recommendations are adopted, supporting ongoing evaluation and review.

Agent Configuration and Governance allow organizations to define analytical resources, test agent behavior, manage access permissions, and refine configurations through evaluation and feedback.

Exploring the Future of AI-Driven Decisions in Barcelona

Smart City Expo World Congress 2026 provided an international setting for discussions about the practical impact of AI, connected data, and digital technologies.

While cities, public institutions, and enterprises operate in different environments, they share an important challenge: transforming fragmented information into decisions that can be understood, evaluated, and acted upon.

For Guandata, the event represented an opportunity to introduce DecideX to a broader international audience and exchange perspectives on how intelligent technologies can support more effective organizational decision-making.

As enterprise AI continues to evolve, Guandata believes the next stage of innovation will be defined not simply by how quickly systems generate answers, but by how reliably they connect business context, evidence, human judgment, and follow-up action.

Looking Ahead: Making Decision Intelligence Practical

Guandata will continue advancing DecideX and its enterprise AI capabilities, focusing on practical adoption within existing business environments.

By combining established data assets with configurable AI agents, business context, decision evidence, and continuous feedback, Guandata aims to help organizations move progressively from data analysis toward more actionable and accountable decision-making.

The future of enterprise AI is not just about generating more insights. It is about helping organizations make better decisions — and learn from what happens next.