Complete Guide to AI on AWS in 2025
Overview of AWS AI Services
AWS offers ready-to-use AI services that don’t require ML expertise.
These services support use cases like speech, vision, language, recommendations, and predictions.
Fully managed, scalable, and accessible via APIs.
Key AWS AI Services and Their Features
Amazon Rekognition
Detects objects, people, text, and unsafe content in images/videos.
Amazon Comprehend
Extracts insights from text: sentiment, key phrases, language.
Amazon Lex
Builds chatbots with automatic speech recognition and NLU.
Amazon Polly
Converts text to natural-sounding speech.
Amazon Transcribe
Converts speech to text with speaker identification.
Amazon Translate
Real-time language translation.
Amazon Personalize
Builds recommendation engines.
Amazon Forecast
Forecasts time series data like inventory, sales, traffic.
Amazon Textract
Extracts structured text and data from scanned docs.
Amazon CodeWhisperer
AI-powered coding assistant in IDEs.
Amazon Bedrock
Provides foundation models (e.g., Anthropic, Meta, Amazon Titan).
Amazon Kendra
Intelligent enterprise search across data sources.
Amazon Fraud Detector
Detects online fraud using ML models.
Real-Time Use Cases
Rekognition — Face match in surveillance.
Comprehend — Analyze customer feedback sentiment.
Lex — Build customer service chatbots.
Polly — Convert books to audio.
Transcribe — Generate transcripts for meetings.
Translate — Real-time translation for global support.
Personalize — Product recommendations on e-commerce sites.
Forecast — Inventory planning for retail.
Textract — Automate invoice and receipt data extraction.
CodeWhisperer — Code suggestions in real-time development.
Bedrock — GenAI chatbots and document summarization.
Kendra — Search internal company documents intelligently.
Fraud Detector — Detect fraudulent credit card transactions.
Cost Analysis (Estimates)
Most services offer free tiers (e.g., 5,000 images for Rekognition, 5M characters for Polly).
Pay-as-you-go pricing (e.g., $1 per 1,000 Rekognition images, $4 per 1M Polly characters).
Bedrock and Personalize are based on usage, tokens, and transactions per second.
Costs vary by region — use the AWS Pricing Calculator for accuracy.
When to Use
When you need quick AI capabilities without building models.
For developers, businesses, and startups aiming to enhance apps with AI.
Ideal for text, voice, vision, and forecasting tasks.
Use SageMaker instead if deep model customization or training is required.
Final Summary
AWS AI Services are ideal for plug-and-play AI features.
No ML expertise needed — easy API integration.
Use them to reduce development time, cost, and complexity.
Great for building smart, scalable, and innovative applicatio
Venkat C S
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