Best Natural Language Generation Software

Compare the Top Natural Language Generation Software as of July 2025

What is Natural Language Generation Software?

Natural language generation software is computer-generated software designed to create natural-sounding output. It can generate text from structured data sources such as databases, or from unstructured sources like audio or video recordings. The output of this software can be used for various tasks such as summarizing information or producing news articles. Natural language generation technology is commonly used in applications that require automated content creation and natural language processing algorithms. Compare and read user reviews of the best Natural Language Generation software currently available using the table below. This list is updated regularly.

  • 1
    LM-Kit.NET
    The on-device NLG module for .NET uses compact local language models to create context-aware text fast and securely. It can generate code snippets, summaries, grammar fixes, and style rewrites without leaving your environment, so data stays private. Use it to automate documents, keep brand voice consistent, and produce multilingual content. Flexible controls let you define formats and styles, making it ideal for reporting, code generation, and concise summaries.
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    Starting Price: Free (Community) or $1000/year
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  • 2
    Google Cloud Natural Language API
    Get insightful text analysis with machine learning that extracts, analyzes, and stores text. Train high-quality machine learning custom models without a single line of code with AutoML. Apply natural language understanding (NLU) to apps with Natural Language API. Use entity analysis to find and label fields within a document, including emails, chat, and social media, and then sentiment analysis to understand customer opinions to find actionable product and UX insights. Natural Language with speech-to-text API extracts insights from audio. Vision API adds optical character recognition (OCR) for scanned docs. Translation API understands sentiments in multiple languages. Use custom entity extraction to identify domain-specific entities within documents, many of which don’t appear in standard language models, without having to spend time or money on manual analysis. Train your own high-quality machine learning custom models to classify, extract, and detect sentiment.
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