Elevate enterprise intelligence with AI built on clean, connected data
Most organizations today aren’t struggling with a lack of data; they’re struggling to make sense of it. Data lives in too many places, often lacks context, and arrives too late to drive meaningful action. That’s why the conversation has shifted from simply collecting data to connecting it and using it in smarter ways.
This is where Infor™ Data Platform really makes a difference. It provides a unified environment where data from multiple sources, both Infor and non-Infor, can be accessed, contextualized, and understood.
When you preserve metadata, lineage, and relationships, data stops being a black box. You’re not just pulling information together; you’re keeping track of where it came from, how it’s changed, and how it connects across your systems. That context makes it possible to trace results back to the source, check accuracy, and trust what you’re using to make decisions.
That matters even more with artificial intelligence (AI). These systems are only as good as the data behind them, and if that data is disconnected, outdated, or poorly understood, things can go wrong fast. The result can be bad insights, hidden bias, and decisions that are difficult to explain or defend.
Without lineage and context, AI can give you answers that sound right but aren’t. Having a strong data foundation isn’t a nice-to-have; it’s what keeps AI useful and trustworthy.
Whether you’re exploring operational trends, analyzing performance metrics, or preparing reports, having this level of clarity and context turns raw data into something meaningful.
Just as importantly, having trusted, well-connected data changes how insights are used. It’s no longer just about looking back at what happened; it’s about enabling teams to respond faster, make better decisions, and act with confidence.
Because data within the platform is already connected, contextualized, and continuously updated, users are no longer limited to predefined dashboards or static reports. Instead, they can engage directly with their data by asking questions, exploring relationships, and generating insights in real time.
This shifts the experience from searching for information to simply interacting with it. Users can quickly generate summaries, uncover patterns, or explore different scenarios without needing to rely on complex tools or start from scratch.
The result is a more flexible and responsive way to work, where data feels less like a system to navigate and more like something you can naturally engage with to make better decisions.
In a traditional analytics workflow, significant time is spent gathering data, validating it, building queries, and refining reports. AI agents streamline that entire process. They can automatically surface relevant datasets, suggest useful metrics, and guide users toward the right analysis based on the context of their question.
Instead of starting with a blank dashboard or report, users can begin with a question, and the agent helps shape the analysis. It can identify trends, highlight anomalies, and even explain what’s driving changes in the data.
Because these agents operate within Infor Data Platform, they leverage underlying metadata, relationships, and lineage to provide more context-aware insights. This allows them to connect data across domains, making it easier to uncover patterns that might otherwise be missed.
When AI agents are grounded in high-quality, well-governed data, their impact extends far beyond analysis. They become active participants in business processes by informing decisions in real time, recommending next best actions, and helping teams respond more quickly to changing conditions.
Whether it’s optimizing operations, improving customer experiences, or guiding financial planning, these agents turn data into continuous, actionable intelligence embedded directly into everyday workflows.
This is where Infor™ Data Platform really makes a difference. It provides a unified environment where data from multiple sources, both Infor and non-Infor, can be accessed, contextualized, and understood.
When you preserve metadata, lineage, and relationships, data stops being a black box. You’re not just pulling information together; you’re keeping track of where it came from, how it’s changed, and how it connects across your systems. That context makes it possible to trace results back to the source, check accuracy, and trust what you’re using to make decisions.
That matters even more with artificial intelligence (AI). These systems are only as good as the data behind them, and if that data is disconnected, outdated, or poorly understood, things can go wrong fast. The result can be bad insights, hidden bias, and decisions that are difficult to explain or defend.
Without lineage and context, AI can give you answers that sound right but aren’t. Having a strong data foundation isn’t a nice-to-have; it’s what keeps AI useful and trustworthy.
Whether you’re exploring operational trends, analyzing performance metrics, or preparing reports, having this level of clarity and context turns raw data into something meaningful.
Turning data into insight, then insight into action
Once that foundation is in place, the real value of connected data starts to emerge. With a data fabric approach bringing consistency and context across systems, analytics becomes more meaningful. Instead of piecing together disconnected reports, teams can work from a unified, reliable view of the business. For example, finance teams can use this foundation to produce more accurate and timely financial reporting, along with clearer visibility into performance drivers. Across the organization, it also strengthens governance by making data easier to trace, validate, and explain, whether for internal decision-making or external audit requirements.Just as importantly, having trusted, well-connected data changes how insights are used. It’s no longer just about looking back at what happened; it’s about enabling teams to respond faster, make better decisions, and act with confidence.
Bringing AI into everyday work
Rather than sitting in separate tools, AI is becoming part of the day-to-day experience. It helps flag anomalies, highlight trends, and suggest next steps right where decisions are being made. This makes data more accessible across the business. You don’t need to be a data scientist to ask better questions or get meaningful answers.A more natural way to work with data
Generative AI (GenAI) builds on the foundation of Infor Data Platform by making interactions with data more intuitive and accessible.Because data within the platform is already connected, contextualized, and continuously updated, users are no longer limited to predefined dashboards or static reports. Instead, they can engage directly with their data by asking questions, exploring relationships, and generating insights in real time.
This shifts the experience from searching for information to simply interacting with it. Users can quickly generate summaries, uncover patterns, or explore different scenarios without needing to rely on complex tools or start from scratch.
The result is a more flexible and responsive way to work, where data feels less like a system to navigate and more like something you can naturally engage with to make better decisions.
How AI agents simplify data and analytics
One of the more powerful shifts happening in data and analytics is the emergence of GenAI agents, which are intelligent assistants that support how users explore and interpret data.In a traditional analytics workflow, significant time is spent gathering data, validating it, building queries, and refining reports. AI agents streamline that entire process. They can automatically surface relevant datasets, suggest useful metrics, and guide users toward the right analysis based on the context of their question.
Instead of starting with a blank dashboard or report, users can begin with a question, and the agent helps shape the analysis. It can identify trends, highlight anomalies, and even explain what’s driving changes in the data.
Because these agents operate within Infor Data Platform, they leverage underlying metadata, relationships, and lineage to provide more context-aware insights. This allows them to connect data across domains, making it easier to uncover patterns that might otherwise be missed.
When AI agents are grounded in high-quality, well-governed data, their impact extends far beyond analysis. They become active participants in business processes by informing decisions in real time, recommending next best actions, and helping teams respond more quickly to changing conditions.
Whether it’s optimizing operations, improving customer experiences, or guiding financial planning, these agents turn data into continuous, actionable intelligence embedded directly into everyday workflows.
Why this matters for your business
When you bring all of this together, a connected data foundation, strong analytics, and embedded AI, the impact is clear:
- Faster, more confident decision-making through contextual, data-driven insights
- Greater efficiency with automation and intelligent workflows
- Enhanced user experience with intuitive, AI-driven interactions
- Clearer, more consistent data for reliable analysis
- Stronger visibility into business performance across domains
- Reduced costs by identifying inefficiencies and mitigating risk
The shift isn’t just about adopting new technology; it’s about changing how organizations work with data altogether. With Infor Data Platform, data becomes more than something you report on. It becomes something you interact with, learn from, and act on every day. That’s where the real value starts to show.