At Maxxified we have been diving into the concepts around AI-Driven Document Classification so now lets look at some of the technology behind that process. With the evolution of automation and Artificial Intelligence, businesses are on the lookout to automate the extraction of relevant and important data from documents. To aid in this, AWS Textract and Comprehend offer different AI-powered solutions, as well as the recently released generative AI model, Bedrock. How do these solutions compare with one another, and which one, if any, is the most economical for businesses that deal with tons of documents? Let us simplify these technologies that AWS offers.
Textract specializes in OCR, meaning it “reads” and processes documents to extract text and data from structured and semi-structured forms such as invoices and forms.
Natural language is processed and comprehended too. Comprehend is another AI powered tool and is good at reading through text, identifying insightful data, and even categorizes the data. It processes sentiment and entity recognition not just dumping text.
Bedrock uses generative AI, meaning, it possesses the ability to Understand a document, Summarize it and even Generate responses pertaining to it, thus, proving itself intelligent with context recognition.
Textract boasts of his capability of accurately extracting text and tables, however, understanding context is not his strong suit.
Comprehend goes a step further by interpreting the meaning of words, entities like names, dates, locations, and even sentiment within the text.
Bedrock epitomizes the most sophisticated at comprehension, as it understands the entire context of a document, summarizes contents, and can even answer questions relating to the document.
Textract and Comprehend are equally scalable, effortlessly handling and processing huge quantities of documents within a short time.
Being a generative AI model, Bedrock requires much greater processing power, which is likely to slow down document processing at extremely high volumes unless properly optimized.
As Textract only centers its focus on the extraction of documents, it is the most economical, especially for bulk processes.
Comprehend’s additional costs stem from the NLP features, which are beneficial for their intelligent categorization but are also an added expense.
Bedrock is the least economical of the three, as generative AI models are more costly due to the increased computing resources and API calls needed for each request. This fact makes Bedrock less suitable for bulk document extraction, regardless of the necessity for more profound insights. The one trend that we will see is that with Bedrock is that cost will go down as more companies start to us the technology.
For companies managing large quantities of documents requiring restively low level data extraction, Textract is the most economical option available. Comprehend is more useful if one analyzes and categorizes text. Nevertheless, those who need to deeply understand context, need summarization, and generative AI capabilities will find Bedrock the perfect option, albeit at a higher price range.
In the end, the appropriate solution varies based on your needs. In case your priority is efficiency at scale, then Textract is the best option for you. If richer data insights is what you seek, then Comprehend or Bedrock would be the better technology options.
At Maxxified, we specialize in empowering businesses through cutting-edge automation and custom cloud-native software solutions. Our mission is to streamline operations, enhance productivity, and drive digital transformation for organizations of all sizes.
With a team of seasoned experts, we deliver tailored software solutions that integrate seamlessly with your existing infrastructure, leveraging the latest technologies to ensure scalability, security, and performance. Our expertise spans a wide range of industries, allowing us to understand the unique challenges and opportunities each sector presents. Intelligence solutions for document classification is what we do! Contact us for a demo now!
