Published Oct 10, 2023 ⦁ 3 min read

Discover the Top 10 Free AI Tools for Developers

Artificial intelligence (AI) technologies like natural language processing (NLP), computer vision (CV), and machine learning (ML) are transforming software applications. With robust AI capabilities now easily accessible, developers are increasingly leveraging them to build smarter, more intuitive apps. This article will highlight 10 leading free tools to add AI superpowers to your projects!

Natural Language Processing

NLP enables analyzing and generating speech and text using AI. Developers employ it for sentiment analysis, summarization, translation, chatbots, and more. Here are 5 top free NLP tools:


DevHunt provides a hosted NLP API for building conversational experiences. It handles speech-to-text, NLU, intent recognition, entity extraction, sentiment analysis, and dialog management. DevHunt is free for up to 100 requests per month.

DevHunt's NLP API allows developers to quickly integrate robust natural language capabilities into their applications. It supports multiple languages and includes powerful features like named entity recognition, content classification, contextual analysis, and flexible dialog management with templating.


SpaCy is an open source NLP library for Python. It can tokenize text, tag parts of speech, recognize named entities, analyze sentiment, and build statistical models. SpaCy integrates word vectors and convolutional neural networks.


AllenNLP provides reference implementations of state-of-the-art NLP models like ELMo, BERT, and GPT-2. It makes model configuration and training easy.


GenSIM is a Python library for topic modeling, document indexing, and similarity retrieval for large datasets. It includes word2vec, doc2vec, TF-IDF, and more.


NLTK provides Python text processing libraries and resources for classification, tokenization, tagging, parsing, and more.

Specialized Tools

Leading free tools for building chatbots and voice assistants include Dialogflow for natural language understanding, Rasa for conversational AI, Amazon Lex for voice/text bots, Azure Bot Service, and IBM Watson Assistant.

For text analysis and classification, options like TextBlob, VADER, CoreNLP, and spaCy provide key capabilities like sentiment analysis, parts-of-speech tagging, named entity recognition, and more.

Computer Vision

CV enables processing, analyzing, and understanding digital images and videos. Developers employ it for facial recognition, object detection, image classification, OCR, and more. Top free CV tools include:

Python Libraries

OpenCV provides extensive algorithms for image and video analysis like facial recognition and object detection. TensorFlow offers end-to-end ML for image classification and object detection. Detectron2 enables high-quality object detection/segmentation.

Cloud Vision APIs

Leading free cloud APIs include Microsoft Azure Computer Vision, Google Cloud Vision, Amazon Rekognition, Clarifai, and Imagga. They provide pre-built models for image/video analysis.

Machine Learning Frameworks

Open source ML frameworks simplify building and deploying models without deep ML expertise. Top free options:


TensorFlow provides extensive tools and resources for ML development. PyTorch enables building deep learning models based on Torch. Keras makes model building/training easier. MXNet is lightweight, portable, and scalable. Scikit-learn offers simple tools for classical ML techniques.


Leading JavaScript ML tools include TensorFlow.js, ML5.js, Brain.js, Synaptic.js, and ConvNetJS. These simplify training/running models in the browser or Node.js.

Next Steps

Hopefully this overview provided some ideas on experimenting with free AI tools in your own projects! As next steps, consider exploring a DevHunt tutorial to see how its conversational AI platform can be leveraged. You can also check out documentation and quickstarts for any of the other tools mentioned above to get hands-on experience with their capabilities.