Natural language generation (NLG) software uses artificial intelligence to interpret structured or unstructured data and automatically present it in easily understood written formats, such as reports, dashboards, or charts, enabling both technical and non-technical users to derive business actions from large data sets.
Core Capabilities of NLG Software
To qualify for inclusion in the Natural Language Generation category, a product must:
- Process data and information using deep learning
- Generate actionable insights from data using deep learning
- Present data in an easily digestible manner for both technical and non-technical users
Common Use Cases for NLG Software
Data scientists, analysts, and business users use NLG software to automatically transform complex data into readable, actionable narratives. Common use cases include:
- Automatically generating written reports and summaries from large structured or unstructured data sets
- Supplementing or supporting data analyst workflows by producing narrative-driven data outputs
- Integrating with BI tools to add natural language narration to dashboards and visualizations
How NLG Software Differs from Other Tools
NLG solutions often work in conjunction with business intelligence software or big data analytics platforms to add automated narrative generation to existing data workflows. Unlike general analytics tools that visualize data, NLG platforms uniquely convert data into written language, making them particularly valuable for organizations that need to communicate data insights to non-technical stakeholders at scale.
Insights from G2 on NLG Software
Based on category trends on G2, the quality of AI-generated narratives and ease of integration with BI platforms stand out as standout features. Time savings in report writing and improved data accessibility for non-technical users as primary outcomes of adoption.