Below are several major categories—each illustrating how AI services are used in concrete ways.

Natural Language Processing & Understanding

- Text classification, sentiment analysis, topic extraction — e.g. tagging support tickets or social media messages.

- Named Entity Recognition (NER) — identifying names, places, dates in text.

- Machine Translation — converting text between languages.

- Summarization, question answering, and text generation — e.g. generating content drafts, chatbots, document summarization.

Conversational & Chatbot Platforms

These services power chat interfaces (text or voice) that understand and respond to users. They often include intent detection, multi-turn dialogue management, and integration with back-end systems. For example, one might embed a conversational agent in a website or app to answer user queries or assist with transactions.

https://overchat.ai/ is a platform in the conversational domain that demonstrates how AI services can power real-time chat automation without needing to build the low-level components oneself.

Computer Vision & Image/Video Processing

- Object detection / image classification — e.g. detecting products on a shelf, classifying medical images.

- Face recognition / facial attributes — identifying who is in a photo, or recognizing emotions.

- Optical Character Recognition (OCR) — extracting text from scanned documents or images.

- Image segmentation, video analytics, anomaly detection in videos.

Speech & Voice

- Speech-to-text transcription — converting spoken words into text.

- Text-to-speech synthesis — generating natural spoken voice from text, often with expressive tone.

- Speaker identification and diarization — recognizing who spoke when.

- Voice conversion, voice cloning — transforming voice style or mimicking a voice.